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CRAN checks API

CRAN checks API is an API providing access to CRAN checks data in a machine-readable format.

For a recent overview of the API, check out the Overview of the CRAN checks API blog post on the R-Hub blog.

The API was created and is maintained by Scott Chamberlain.

Base URL

https://cranchecks.info/

R package cchecks 📦

Most endpoints are supported in the cchecks R client.

remotes::install_github("ropenscilabs/cchecks")
library("cchecks")

Authentication

Endpoints without authentication

docs/, heartbeat/, maintainers/, packages/, history/, badges/, search/

Endpoints with authentication

notifications/

HTTP methods

This is mostly a read only API. That is, we only allow GET (and HEAD) requests on this API.

Requests of all other types will be rejected with appropriate 405 code.

Media types

JSON mostly, image/svg+xml for badges.

Pagination

The query parameters limit (default = 10) and offset (default = 0) can be sent.

limit (integer, optional)
number of records to return. Default: 10. Max: see endpoint docs.
offset (integer, optional)
Record number to start at. Default: 0. Max: see endpoint docs.

Above parameters can be used only on /pkgs, /maintainers, and /pkgs/{package_name}/history.

The response body from the server will include data on records found in found and number returned in count.

Response codes

For this section of the docs, examples of (bad) requests are given in the Shell tab on the right, and the headers are in the Headers tab.

200 (OK)

Request good!

curl https://cranchecks.info/heartbeat | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 256
date: Mon, 15 Mar 2021 12:59:43 GMT

{
    "routes": [
        "/",
        "/docs",
        "/heartbeat/?",
        "/pkgs",
        "/pkgs/:name",
        "/maintainers",
        "/maintainers/:email",
        "/badges/:type/:package",
        "/badges/flavor/:flavor/:package",
        "/pkgs/:name/history",
        "/history/:date",
        "/search",
        "/notifications/rules",
        "/notifications/rules/:id"
    ]
}

204 (No Content)

Given on a delete request, indicating success, response body should be empty.

curl -XDELETE -H "Authorization: Bearer ***" \
 https://cranchecks.info/notifications/rules/512
HTTP/2 204 
access-control-allow-methods: DELETE
server: Caddy
x-content-type-options: nosniff
date: Mon, 15 Mar 2021 12:59:43 GMT

302 (Found)

The root /, redirects to /heartbeat, and /docs redirects to what you’re reading right now.

curl https://cranchecks.info/ | jq .
HTTP/2 302 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://cranchecks.info/heartbeat
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 15 Mar 2021 12:59:43 GMT

400 (Bad request)

When you have a malformed request, fix it and try again

curl https://cranchecks.info/maintainers/blablabla | jq .
HTTP/2 400 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 52
date: Mon, 15 Mar 2021 12:59:44 GMT

{
    "error": {
        "message": "no results found"
    },
    "data": null
}

404 (Not found)

When you request a route that does not exist, fix it and try again. E.g. in the example here we misspell “maintainers” to “maintainer”. 🙈

curl https://cranchecks.info/maintainer | jq .
HTTP/2 404 
content-type: application/json
server: Caddy
x-cascade: pass
x-content-type-options: nosniff
content-length: 27
date: Mon, 15 Mar 2021 12:59:44 GMT

{
    "error": "route not found"
}

405 (Method not allowed)

When you use a prohibited HTTP method for a given route. Don’t do that. 😉

curl -XDELETE https://cranchecks.info/pkgs/ropenaq/
HTTP/2 405 
content-type: application/json
server: Caddy
x-content-type-options: nosniff
content-length: 30
date: Mon, 15 Mar 2021 12:59:44 GMT

{
    "error": "Method Not Allowed"
}

500 (Internal server error)

Server got itself in trouble 😱 😭; get in touch with us.

HTTP/2 500
date: Thu, 21 May 2020 16:53:33 GMT
content-type: text/html; charset=utf-8
content-length: 0

Root

This path redirects to /heartbeat

curl https://cranchecks.info/ | jq .
HTTP/2 302 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://cranchecks.info/heartbeat
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 15 Mar 2021 12:59:44 GMT

Heartbeat

Get heartbeat for the API 💓 (i.e. the list of endpoints).

GET [/heartbeat]

Function of the cchecks R package: cch_heartbeat().

curl https://cranchecks.info/heartbeat | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 256
date: Mon, 15 Mar 2021 12:59:32 GMT

{
    "routes": [
        "/",
        "/docs",
        "/heartbeat/?",
        "/pkgs",
        "/pkgs/:name",
        "/maintainers",
        "/maintainers/:email",
        "/badges/:type/:package",
        "/badges/flavor/:flavor/:package",
        "/pkgs/:name/history",
        "/history/:date",
        "/search",
        "/notifications/rules",
        "/notifications/rules/:id"
    ]
}
cchecks::cch_heartbeat()
$routes
 [1] "/"                               "/docs"                          
 [3] "/heartbeat/?"                    "/pkgs"                          
 [5] "/pkgs/:name"                     "/maintainers"                   
 [7] "/maintainers/:email"             "/badges/:type/:package"         
 [9] "/badges/flavor/:flavor/:package" "/pkgs/:name/history"            
[11] "/history/:date"                  "/search"                        
[13] "/notifications/rules"            "/notifications/rules/:id"       

Docs

This path redirects to the docs (hopefully here! 😸). See Headers tab.

GET [/docs]

curl https://cranchecks.info/docs
HTTP/2 301 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
location: https://docs.cranchecks.info/
server: Caddy
x-content-type-options: nosniff
content-length: 0
date: Mon, 15 Mar 2021 12:59:32 GMT

Maintainers

Get checks data by package maintainer.

Function of the cchecks R package: cch_maintainers().

Maintainers

Get checks summaries for all maintainers.

GET [/maintainers]

Default limit of 10, max of 1000.

Example with custom offset and limit.

curl https://cranchecks.info/maintainers/?limit=2&offset=5 | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 1060
date: Mon, 15 Mar 2021 12:59:35 GMT

{
    "found": 10726,
    "count": 2,
    "offset": 5,
    "error": null,
    "data": [
        {
            "email": "markus.boenn.sf_at_googlemail.com",
            "name": "Markus Boenn",
            "url": "https://cloud.r-project.org/web/checks/check_results_markus.boenn.sf_at_googlemail.com.html",
            "date_updated": "2021-03-05T12:02:37.426Z",
            "table": [
                {
                    "package": "hypergea",
                    "any": true,
                    "ok": 6,
                    "note": 6,
                    "warn": 0,
                    "error": 0
                }
            ],
            "packages": [
                {
                    "package": "hypergea",
                    "url": "https://cloud.r-project.org/web/checks/check_results_hypergea.html",
                    "check_result": [
                        {
                            "category": "NOTE",
                            "number_checks": 6
                        },
                        {
                            "category": "OK",
                            "number_checks": 6
                        }
                    ],
                    "version": null
                }
            ]
        },
        {
            "email": "s.greilich_at_dkfz.de",
            "name": "Steffen Greilich",
            "url": "https://cloud.r-project.org/web/checks/check_results_s.greilich_at_dkfz.de.html",
            "date_updated": "2021-03-05T12:02:37.426Z",
            "table": [
                {
                    "package": "libamtrack",
                    "any": true,
                    "ok": 2,
                    "note": 10,
                    "warn": 0,
                    "error": 0
                }
            ],
            "packages": [
                {
                    "package": "libamtrack",
                    "url": "https://cloud.r-project.org/web/checks/check_results_libamtrack.html",
                    "check_result": [
                        {
                            "category": "NOTE",
                            "number_checks": 10
                        },
                        {
                            "category": "OK",
                            "number_checks": 2
                        }
                    ],
                    "version": null
                }
            ]
        }
    ]
}
cchecks::cch_maintainers(limit = 2, offset = 5)
$found
[1] 10726

$count
[1] 2

$offset
[1] 5

$error
NULL

$data
                              email             name
1 markus.boenn.sf_at_googlemail.com     Markus Boenn
2             s.greilich_at_dkfz.de Steffen Greilich
                                                                                          url
1 https://cloud.r-project.org/web/checks/check_results_markus.boenn.sf_at_googlemail.com.html
2             https://cloud.r-project.org/web/checks/check_results_s.greilich_at_dkfz.de.html
              date_updated                         table
1 2021-03-05T12:02:37.426Z    hypergea, TRUE, 6, 6, 0, 0
2 2021-03-05T12:02:37.426Z libamtrack, TRUE, 2, 10, 0, 0
                                                                                               packages
1      hypergea, https://cloud.r-project.org/web/checks/check_results_hypergea.html, NOTE, OK, 6, 6, NA
2 libamtrack, https://cloud.r-project.org/web/checks/check_results_libamtrack.html, NOTE, OK, 10, 2, NA

Maintainers by email

Get checks data by email of the package maintainer.

GET [/maintainers/{email}]

⚠️ jane.doe@example.com has to be transformed to jane.doe_at_example.com.

curl https://cranchecks.info/maintainers/csardi.gabor_at_gmail.com | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 13628
date: Mon, 15 Mar 2021 12:59:36 GMT

{
    "error": null,
    "data": {
        "email": "csardi.gabor_at_gmail.com",
        "name": "Gábor Csárdi",
        "url": "https://cloud.r-project.org/web/checks/check_results_csardi.gabor_at_gmail.com.html",
        "date_updated": "2021-03-05T12:02:37.986Z",
        "table": [
            {
                "package": "asciicast",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "callr",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "cleancall",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "cli",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "cliapp",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "clisymbols",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "cranlike",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "cranlogs",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "crayon",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "debugme",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "desc",
                "any": true,
                "ok": 11,
                "note": 0,
                "warn": 0,
                "error": 1
            },
            {
                "package": "disposables",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "dotenv",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "filelock",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "franc",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "gh",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "gitcreds",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "igraph",
                "any": true,
                "ok": 5,
                "note": 7,
                "warn": 0,
                "error": 0
            },
            {
                "package": "igraphdata",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "isa2",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "keypress",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "keyring",
                "any": true,
                "ok": 10,
                "note": 2,
                "warn": 0,
                "error": 0
            },
            {
                "package": "liteq",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "lpSolve",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "oskeyring",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "pak",
                "any": true,
                "ok": 11,
                "note": 1,
                "warn": 0,
                "error": 0
            },
            {
                "package": "parsedate",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "pingr",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "pkgcache",
                "any": true,
                "ok": 11,
                "note": 0,
                "warn": 0,
                "error": 1
            },
            {
                "package": "pkgconfig",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "pkgsearch",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "praise",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "presser",
                "any": true,
                "ok": 11,
                "note": 0,
                "warn": 0,
                "error": 1
            },
            {
                "package": "prettycode",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "prettyunits",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "processx",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "progress",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "prompt",
                "any": true,
                "ok": 2,
                "note": 0,
                "warn": 0,
                "error": 1
            },
            {
                "package": "ps",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "rcmdcheck",
                "any": true,
                "ok": 11,
                "note": 1,
                "warn": 0,
                "error": 0
            },
            {
                "package": "rcorpora",
                "any": true,
                "ok": 5,
                "note": 7,
                "warn": 0,
                "error": 0
            },
            {
                "package": "rematch2",
                "any": true,
                "ok": 11,
                "note": 1,
                "warn": 0,
                "error": 0
            },
            {
                "package": "rhub",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "rversions",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "sankey",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "secret",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "sessioninfo",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "showimage",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "tracer",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "webdriver",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "webfakes",
                "any": true,
                "ok": 11,
                "note": 0,
                "warn": 0,
                "error": 1
            },
            {
                "package": "whoami",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "xmlparsedata",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "xopen",
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0
            },
            {
                "package": "zip",
                "any": true,
                "ok": 11,
                "note": 0,
                "warn": 0,
                "error": 1
            }
        ],
        "packages": [
            {
                "package": "asciicast",
                "url": "https://cloud.r-project.org/web/checks/check_results_asciicast.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "callr",
                "url": "https://cloud.r-project.org/web/checks/check_results_callr.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "cleancall",
                "url": "https://cloud.r-project.org/web/checks/check_results_cleancall.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "cli",
                "url": "https://cloud.r-project.org/web/checks/check_results_cli.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "cliapp",
                "url": "https://cloud.r-project.org/web/checks/check_results_cliapp.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "clisymbols",
                "url": "https://cloud.r-project.org/web/checks/check_results_clisymbols.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "cranlike",
                "url": "https://cloud.r-project.org/web/checks/check_results_cranlike.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "cranlogs",
                "url": "https://cloud.r-project.org/web/checks/check_results_cranlogs.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "crayon",
                "url": "https://cloud.r-project.org/web/checks/check_results_crayon.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "debugme",
                "url": "https://cloud.r-project.org/web/checks/check_results_debugme.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "desc",
                "url": "https://cloud.r-project.org/web/checks/check_results_desc.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "disposables",
                "url": "https://cloud.r-project.org/web/checks/check_results_disposables.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "dotenv",
                "url": "https://cloud.r-project.org/web/checks/check_results_dotenv.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "filelock",
                "url": "https://cloud.r-project.org/web/checks/check_results_filelock.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "franc",
                "url": "https://cloud.r-project.org/web/checks/check_results_franc.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "gh",
                "url": "https://cloud.r-project.org/web/checks/check_results_gh.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "gitcreds",
                "url": "https://cloud.r-project.org/web/checks/check_results_gitcreds.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "igraph",
                "url": "https://cloud.r-project.org/web/checks/check_results_igraph.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 7
                    },
                    {
                        "category": "OK",
                        "number_checks": 5
                    }
                ],
                "version": null
            },
            {
                "package": "igraphdata",
                "url": "https://cloud.r-project.org/web/checks/check_results_igraphdata.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "isa2",
                "url": "https://cloud.r-project.org/web/checks/check_results_isa2.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "keypress",
                "url": "https://cloud.r-project.org/web/checks/check_results_keypress.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "keyring",
                "url": "https://cloud.r-project.org/web/checks/check_results_keyring.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 2
                    },
                    {
                        "category": "OK",
                        "number_checks": 10
                    }
                ],
                "version": null
            },
            {
                "package": "liteq",
                "url": "https://cloud.r-project.org/web/checks/check_results_liteq.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "lpSolve",
                "url": "https://cloud.r-project.org/web/checks/check_results_lpSolve.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "oskeyring",
                "url": "https://cloud.r-project.org/web/checks/check_results_oskeyring.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "pak",
                "url": "https://cloud.r-project.org/web/checks/check_results_pak.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "parsedate",
                "url": "https://cloud.r-project.org/web/checks/check_results_parsedate.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "pingr",
                "url": "https://cloud.r-project.org/web/checks/check_results_pingr.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "pkgcache",
                "url": "https://cloud.r-project.org/web/checks/check_results_pkgcache.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "pkgconfig",
                "url": "https://cloud.r-project.org/web/checks/check_results_pkgconfig.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "pkgsearch",
                "url": "https://cloud.r-project.org/web/checks/check_results_pkgsearch.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "praise",
                "url": "https://cloud.r-project.org/web/checks/check_results_praise.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "presser",
                "url": "https://cloud.r-project.org/web/checks/check_results_presser.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "prettycode",
                "url": "https://cloud.r-project.org/web/checks/check_results_prettycode.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "prettyunits",
                "url": "https://cloud.r-project.org/web/checks/check_results_prettyunits.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "processx",
                "url": "https://cloud.r-project.org/web/checks/check_results_processx.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "progress",
                "url": "https://cloud.r-project.org/web/checks/check_results_progress.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "prompt",
                "url": "https://cloud.r-project.org/web/checks/check_results_prompt.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 2
                    }
                ],
                "version": null
            },
            {
                "package": "ps",
                "url": "https://cloud.r-project.org/web/checks/check_results_ps.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "rcmdcheck",
                "url": "https://cloud.r-project.org/web/checks/check_results_rcmdcheck.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "rcorpora",
                "url": "https://cloud.r-project.org/web/checks/check_results_rcorpora.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 7
                    },
                    {
                        "category": "OK",
                        "number_checks": 5
                    }
                ],
                "version": null
            },
            {
                "package": "rematch2",
                "url": "https://cloud.r-project.org/web/checks/check_results_rematch2.html",
                "check_result": [
                    {
                        "category": "NOTE",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "rhub",
                "url": "https://cloud.r-project.org/web/checks/check_results_rhub.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "rversions",
                "url": "https://cloud.r-project.org/web/checks/check_results_rversions.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "sankey",
                "url": "https://cloud.r-project.org/web/checks/check_results_sankey.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "secret",
                "url": "https://cloud.r-project.org/web/checks/check_results_secret.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "sessioninfo",
                "url": "https://cloud.r-project.org/web/checks/check_results_sessioninfo.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "showimage",
                "url": "https://cloud.r-project.org/web/checks/check_results_showimage.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "tracer",
                "url": "https://cloud.r-project.org/web/checks/check_results_tracer.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "webdriver",
                "url": "https://cloud.r-project.org/web/checks/check_results_webdriver.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "webfakes",
                "url": "https://cloud.r-project.org/web/checks/check_results_webfakes.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            },
            {
                "package": "whoami",
                "url": "https://cloud.r-project.org/web/checks/check_results_whoami.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "xmlparsedata",
                "url": "https://cloud.r-project.org/web/checks/check_results_xmlparsedata.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "xopen",
                "url": "https://cloud.r-project.org/web/checks/check_results_xopen.html",
                "check_result": [
                    {
                        "category": "OK",
                        "number_checks": 12
                    }
                ],
                "version": null
            },
            {
                "package": "zip",
                "url": "https://cloud.r-project.org/web/checks/check_results_zip.html",
                "check_result": [
                    {
                        "category": "ERROR",
                        "number_checks": 1
                    },
                    {
                        "category": "OK",
                        "number_checks": 11
                    }
                ],
                "version": null
            }
        ]
    }
}
cchecks::cch_maintainers(x = "csardi.gabor_at_gmail.com")
$error
NULL

$data
$data$email
[1] "csardi.gabor_at_gmail.com"

$data$name
[1] "Gábor Csárdi"

$data$url
[1] "https://cloud.r-project.org/web/checks/check_results_csardi.gabor_at_gmail.com.html"

$data$date_updated
[1] "2021-03-05T12:02:37.986Z"

$data$table
        package   any ok note warn error
1     asciicast FALSE 12    0    0     0
2         callr FALSE 12    0    0     0
3     cleancall FALSE 12    0    0     0
4           cli FALSE 12    0    0     0
5        cliapp FALSE 12    0    0     0
6    clisymbols FALSE 12    0    0     0
7      cranlike FALSE 12    0    0     0
8      cranlogs FALSE 12    0    0     0
9        crayon FALSE 12    0    0     0
10      debugme FALSE 12    0    0     0
11         desc  TRUE 11    0    0     1
12  disposables FALSE 12    0    0     0
13       dotenv FALSE 12    0    0     0
14     filelock FALSE 12    0    0     0
15        franc FALSE 12    0    0     0
16           gh FALSE 12    0    0     0
17     gitcreds FALSE 12    0    0     0
18       igraph  TRUE  5    7    0     0
19   igraphdata FALSE 12    0    0     0
20         isa2 FALSE 12    0    0     0
21     keypress FALSE 12    0    0     0
22      keyring  TRUE 10    2    0     0
23        liteq FALSE 12    0    0     0
24      lpSolve FALSE 12    0    0     0
25    oskeyring FALSE 12    0    0     0
26          pak  TRUE 11    1    0     0
27    parsedate FALSE 12    0    0     0
28        pingr FALSE 12    0    0     0
29     pkgcache  TRUE 11    0    0     1
30    pkgconfig FALSE 12    0    0     0
31    pkgsearch FALSE 12    0    0     0
32       praise FALSE 12    0    0     0
33      presser  TRUE 11    0    0     1
34   prettycode FALSE 12    0    0     0
35  prettyunits FALSE 12    0    0     0
36     processx FALSE 12    0    0     0
37     progress FALSE 12    0    0     0
38       prompt  TRUE  2    0    0     1
39           ps FALSE 12    0    0     0
40    rcmdcheck  TRUE 11    1    0     0
41     rcorpora  TRUE  5    7    0     0
42     rematch2  TRUE 11    1    0     0
43         rhub FALSE 12    0    0     0
44    rversions FALSE 12    0    0     0
45       sankey FALSE 12    0    0     0
46       secret FALSE 12    0    0     0
47  sessioninfo FALSE 12    0    0     0
48    showimage FALSE 12    0    0     0
49       tracer FALSE 12    0    0     0
50    webdriver FALSE 12    0    0     0
51     webfakes  TRUE 11    0    0     1
52       whoami FALSE 12    0    0     0
53 xmlparsedata FALSE 12    0    0     0
54        xopen FALSE 12    0    0     0
55          zip  TRUE 11    0    0     1

$data$packages
        package
1     asciicast
2         callr
3     cleancall
4           cli
5        cliapp
6    clisymbols
7      cranlike
8      cranlogs
9        crayon
10      debugme
11         desc
12  disposables
13       dotenv
14     filelock
15        franc
16           gh
17     gitcreds
18       igraph
19   igraphdata
20         isa2
21     keypress
22      keyring
23        liteq
24      lpSolve
25    oskeyring
26          pak
27    parsedate
28        pingr
29     pkgcache
30    pkgconfig
31    pkgsearch
32       praise
33      presser
34   prettycode
35  prettyunits
36     processx
37     progress
38       prompt
39           ps
40    rcmdcheck
41     rcorpora
42     rematch2
43         rhub
44    rversions
45       sankey
46       secret
47  sessioninfo
48    showimage
49       tracer
50    webdriver
51     webfakes
52       whoami
53 xmlparsedata
54        xopen
55          zip
                                                                      url
1     https://cloud.r-project.org/web/checks/check_results_asciicast.html
2         https://cloud.r-project.org/web/checks/check_results_callr.html
3     https://cloud.r-project.org/web/checks/check_results_cleancall.html
4           https://cloud.r-project.org/web/checks/check_results_cli.html
5        https://cloud.r-project.org/web/checks/check_results_cliapp.html
6    https://cloud.r-project.org/web/checks/check_results_clisymbols.html
7      https://cloud.r-project.org/web/checks/check_results_cranlike.html
8      https://cloud.r-project.org/web/checks/check_results_cranlogs.html
9        https://cloud.r-project.org/web/checks/check_results_crayon.html
10      https://cloud.r-project.org/web/checks/check_results_debugme.html
11         https://cloud.r-project.org/web/checks/check_results_desc.html
12  https://cloud.r-project.org/web/checks/check_results_disposables.html
13       https://cloud.r-project.org/web/checks/check_results_dotenv.html
14     https://cloud.r-project.org/web/checks/check_results_filelock.html
15        https://cloud.r-project.org/web/checks/check_results_franc.html
16           https://cloud.r-project.org/web/checks/check_results_gh.html
17     https://cloud.r-project.org/web/checks/check_results_gitcreds.html
18       https://cloud.r-project.org/web/checks/check_results_igraph.html
19   https://cloud.r-project.org/web/checks/check_results_igraphdata.html
20         https://cloud.r-project.org/web/checks/check_results_isa2.html
21     https://cloud.r-project.org/web/checks/check_results_keypress.html
22      https://cloud.r-project.org/web/checks/check_results_keyring.html
23        https://cloud.r-project.org/web/checks/check_results_liteq.html
24      https://cloud.r-project.org/web/checks/check_results_lpSolve.html
25    https://cloud.r-project.org/web/checks/check_results_oskeyring.html
26          https://cloud.r-project.org/web/checks/check_results_pak.html
27    https://cloud.r-project.org/web/checks/check_results_parsedate.html
28        https://cloud.r-project.org/web/checks/check_results_pingr.html
29     https://cloud.r-project.org/web/checks/check_results_pkgcache.html
30    https://cloud.r-project.org/web/checks/check_results_pkgconfig.html
31    https://cloud.r-project.org/web/checks/check_results_pkgsearch.html
32       https://cloud.r-project.org/web/checks/check_results_praise.html
33      https://cloud.r-project.org/web/checks/check_results_presser.html
34   https://cloud.r-project.org/web/checks/check_results_prettycode.html
35  https://cloud.r-project.org/web/checks/check_results_prettyunits.html
36     https://cloud.r-project.org/web/checks/check_results_processx.html
37     https://cloud.r-project.org/web/checks/check_results_progress.html
38       https://cloud.r-project.org/web/checks/check_results_prompt.html
39           https://cloud.r-project.org/web/checks/check_results_ps.html
40    https://cloud.r-project.org/web/checks/check_results_rcmdcheck.html
41     https://cloud.r-project.org/web/checks/check_results_rcorpora.html
42     https://cloud.r-project.org/web/checks/check_results_rematch2.html
43         https://cloud.r-project.org/web/checks/check_results_rhub.html
44    https://cloud.r-project.org/web/checks/check_results_rversions.html
45       https://cloud.r-project.org/web/checks/check_results_sankey.html
46       https://cloud.r-project.org/web/checks/check_results_secret.html
47  https://cloud.r-project.org/web/checks/check_results_sessioninfo.html
48    https://cloud.r-project.org/web/checks/check_results_showimage.html
49       https://cloud.r-project.org/web/checks/check_results_tracer.html
50    https://cloud.r-project.org/web/checks/check_results_webdriver.html
51     https://cloud.r-project.org/web/checks/check_results_webfakes.html
52       https://cloud.r-project.org/web/checks/check_results_whoami.html
53 https://cloud.r-project.org/web/checks/check_results_xmlparsedata.html
54        https://cloud.r-project.org/web/checks/check_results_xopen.html
55          https://cloud.r-project.org/web/checks/check_results_zip.html
       check_result version
1            OK, 12      NA
2            OK, 12      NA
3            OK, 12      NA
4            OK, 12      NA
5            OK, 12      NA
6            OK, 12      NA
7            OK, 12      NA
8            OK, 12      NA
9            OK, 12      NA
10           OK, 12      NA
11 ERROR, OK, 1, 11      NA
12           OK, 12      NA
13           OK, 12      NA
14           OK, 12      NA
15           OK, 12      NA
16           OK, 12      NA
17           OK, 12      NA
18   NOTE, OK, 7, 5      NA
19           OK, 12      NA
20           OK, 12      NA
21           OK, 12      NA
22  NOTE, OK, 2, 10      NA
23           OK, 12      NA
24           OK, 12      NA
25           OK, 12      NA
26  NOTE, OK, 1, 11      NA
27           OK, 12      NA
28           OK, 12      NA
29 ERROR, OK, 1, 11      NA
30           OK, 12      NA
31           OK, 12      NA
32           OK, 12      NA
33 ERROR, OK, 1, 11      NA
34           OK, 12      NA
35           OK, 12      NA
36           OK, 12      NA
37           OK, 12      NA
38  ERROR, OK, 1, 2      NA
39           OK, 12      NA
40  NOTE, OK, 1, 11      NA
41   NOTE, OK, 7, 5      NA
42  NOTE, OK, 1, 11      NA
43           OK, 12      NA
44           OK, 12      NA
45           OK, 12      NA
46           OK, 12      NA
47           OK, 12      NA
48           OK, 12      NA
49           OK, 12      NA
50           OK, 12      NA
51 ERROR, OK, 1, 11      NA
52           OK, 12      NA
53           OK, 12      NA
54           OK, 12      NA
55 ERROR, OK, 1, 11      NA

Packages

Get packages based checks.

Function of the cchecks R package: cch_pkgs().

Packages

Get checks data for all packages.

GET [/pkgs] Default limit of 10, max of 1000.

Example with custom offset and limit.

curl https://cranchecks.info/pkgs/?offset=5&limit=2 | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 6143
date: Mon, 15 Mar 2021 12:59:41 GMT

{
    "found": 18710,
    "count": 2,
    "offset": 5,
    "error": null,
    "data": [
        {
            "package": "quantable",
            "url": "https://cloud.r-project.org/web/checks/check_results_quantable.html",
            "date_updated": "2021-03-15T12:04:30.994Z",
            "summary": {
                "any": false,
                "ok": 12,
                "note": 0,
                "warn": 0,
                "error": 0,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "0.3.6",
                    "tinstall": 15.56,
                    "tcheck": 147.57,
                    "ttotal": 163.13,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/quantable-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "0.3.6",
                    "tinstall": 12.55,
                    "tcheck": 109.69,
                    "ttotal": 122.24,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/quantable-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 196.99,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/quantable-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 188.28,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/quantable-00check.html"
                },
                {
                    "flavor": "r-devel-windows-x86_64-gcc10-UCRT",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/quantable-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "0.3.6",
                    "tinstall": 12.83,
                    "tcheck": 137.4,
                    "ttotal": 150.23,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/quantable-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 276.2,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/quantable-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "0.3.6",
                    "tinstall": 13.63,
                    "tcheck": 137.83,
                    "ttotal": 151.46,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/quantable-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/quantable-00check.html"
                },
                {
                    "flavor": "r-release-windows-ix86+x86_64",
                    "version": "0.3.6",
                    "tinstall": 38,
                    "tcheck": 137,
                    "ttotal": 175,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/quantable-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "0.3.6",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/quantable-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "0.3.6",
                    "tinstall": 25,
                    "tcheck": 156,
                    "ttotal": 181,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/quantable-00check.html"
                }
            ],
            "check_details": null
        },
        {
            "package": "ibb",
            "url": "https://cloud.r-project.org/web/checks/check_results_ibb.html",
            "date_updated": "2021-03-15T12:04:30.994Z",
            "summary": {
                "any": true,
                "ok": 6,
                "note": 6,
                "warn": 0,
                "error": 0,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "0.0.2",
                    "tinstall": 2.15,
                    "tcheck": 27.83,
                    "ttotal": 29.98,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/ibb-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "0.0.2",
                    "tinstall": 1.59,
                    "tcheck": 21.98,
                    "ttotal": 23.57,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/ibb-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 46.68,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/ibb-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 36.35,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/ibb-00check.html"
                },
                {
                    "flavor": "r-devel-windows-ix86+x86_64",
                    "version": "0.0.2",
                    "tinstall": 6,
                    "tcheck": 54,
                    "ttotal": 60,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/ibb-00check.html"
                },
                {
                    "flavor": "r-devel-windows-x86_64-gcc10-UCRT",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/ibb-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "0.0.2",
                    "tinstall": 2.39,
                    "tcheck": 27.52,
                    "ttotal": 29.91,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/ibb-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 55.8,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/ibb-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "0.0.2",
                    "tinstall": 2.33,
                    "tcheck": 27.39,
                    "ttotal": 29.72,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/ibb-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/ibb-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "0.0.2",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/ibb-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "0.0.2",
                    "tinstall": 3,
                    "tcheck": 34,
                    "ttotal": 37,
                    "status": "OK",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/ibb-00check.html"
                }
            ],
            "check_details": {
                "details": [
                    {
                        "version": "0.0.2",
                        "output": "  Note: found 359 marked UTF-8 strings",
                        "check": "data for non-ASCII characters",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-x86_64-gcc10-UCRT",
                            "r-patched-solaris-x86",
                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
                        ]
                    }
                ],
                "additional_issues": null
            }
        }
    ]
}
cchecks::cch_pkgs(
  limit = 2, 
  offset = 5
  )
$found
[1] 18710

$count
[1] 2

$offset
[1] 5

$error
NULL

$data
    package                                                                 url
1 quantable https://cloud.r-project.org/web/checks/check_results_quantable.html
2       ibb       https://cloud.r-project.org/web/checks/check_results_ibb.html
              date_updated summary.any summary.ok summary.note summary.warn
1 2021-03-15T12:04:30.994Z       FALSE         12            0            0
2 2021-03-15T12:04:30.994Z        TRUE          6            6            0
  summary.error summary.fail
1             0            0
2             0            0
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         checks
1 r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64-gcc10-UCRT, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 0.3.6, 15.56, 12.55, 0, 0, 0, 12.83, 0, 13.63, 0, 38, 0, 25, 147.57, 109.69, 0, 0, 0, 137.4, 0, 137.83, 0, 137, 0, 156, 163.13, 122.24, 196.99, 188.28, 0, 150.23, 276.2, 151.46, 0, 175, 0, 181, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, OK, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/quantable-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/quantable-00check.html
2                                                                                     r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-x86_64-gcc10-UCRT, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 0.0.2, 2.15, 1.59, 0, 0, 6, 0, 2.39, 0, 2.33, 0, 0, 3, 27.83, 21.98, 0, 0, 54, 0, 27.52, 0, 27.39, 0, 0, 34, 29.98, 23.57, 46.68, 36.35, 60, 0, 29.91, 55.8, 29.72, 0, 0, 37, OK, OK, NOTE, NOTE, OK, NOTE, OK, NOTE, OK, NOTE, NOTE, OK, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/ibb-00check.html, https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/ibb-00check.html
                                                                                                                                                                                                                                      check_details.details
1                                                                                                                                                                                                                                                      NULL
2 0.0.2,   Note: found 359 marked UTF-8 strings, data for non-ASCII characters, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64-gcc10-UCRT, r-patched-solaris-x86, r-release-macos-x86_64, r-oldrel-macos-x86_64
  check_details.additional_issues
1                              NA
2                              NA

Packages by name

Get checks summary by package name.

Function of the cchecks package: cch_pkgs_history()

GET [/pkgs/{package}]

curl https://cranchecks.info/pkgs/rhub | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 2632
date: Mon, 15 Mar 2021 12:59:41 GMT

{
    "error": null,
    "data": {
        "package": "rhub",
        "url": "https://cloud.r-project.org/web/checks/check_results_rhub.html",
        "date_updated": "2021-03-15T12:04:31.253Z",
        "summary": {
            "any": false,
            "ok": 11,
            "note": 0,
            "warn": 0,
            "error": 0,
            "fail": 0
        },
        "checks": [
            {
                "flavor": "r-devel-linux-x86_64-debian-clang",
                "version": "1.1.1",
                "tinstall": 7.37,
                "tcheck": 50.55,
                "ttotal": 57.92,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/rhub-00check.html"
            },
            {
                "flavor": "r-devel-linux-x86_64-debian-gcc",
                "version": "1.1.1",
                "tinstall": 5.14,
                "tcheck": 38.75,
                "ttotal": 43.89,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html"
            },
            {
                "flavor": "r-devel-linux-x86_64-fedora-clang",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 78.32,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html"
            },
            {
                "flavor": "r-devel-linux-x86_64-fedora-gcc",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 83.47,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html"
            },
            {
                "flavor": "r-devel-windows-x86_64-gcc10-UCRT",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 0,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html"
            },
            {
                "flavor": "r-patched-linux-x86_64",
                "version": "1.1.1",
                "tinstall": 7.55,
                "tcheck": 49.01,
                "ttotal": 56.56,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html"
            },
            {
                "flavor": "r-patched-solaris-x86",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 89.8,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html"
            },
            {
                "flavor": "r-release-linux-x86_64",
                "version": "1.1.1",
                "tinstall": 7.1,
                "tcheck": 48.8,
                "ttotal": 55.9,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html"
            },
            {
                "flavor": "r-release-macos-x86_64",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 0,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html"
            },
            {
                "flavor": "r-oldrel-macos-x86_64",
                "version": "1.1.1",
                "tinstall": 0,
                "tcheck": 0,
                "ttotal": 0,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/rhub-00check.html"
            },
            {
                "flavor": "r-oldrel-windows-ix86+x86_64",
                "version": "1.1.1",
                "tinstall": 8,
                "tcheck": 60,
                "ttotal": 68,
                "status": "OK",
                "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/rhub-00check.html"
            }
        ],
        "check_details": null
    }
}
cchecks::cch_pkgs(x = "rhub")
$error
NULL

$data
$data$package
[1] "rhub"

$data$url
[1] "https://cloud.r-project.org/web/checks/check_results_rhub.html"

$data$date_updated
[1] "2021-03-15T12:04:31.253Z"

$data$summary
$data$summary$any
[1] FALSE

$data$summary$ok
[1] 11

$data$summary$note
[1] 0

$data$summary$warn
[1] 0

$data$summary$error
[1] 0

$data$summary$fail
[1] 0


$data$checks
                              flavor version tinstall tcheck ttotal status
1  r-devel-linux-x86_64-debian-clang   1.1.1     7.37  50.55  57.92     OK
2    r-devel-linux-x86_64-debian-gcc   1.1.1     5.14  38.75  43.89     OK
3  r-devel-linux-x86_64-fedora-clang   1.1.1     0.00   0.00  78.32     OK
4    r-devel-linux-x86_64-fedora-gcc   1.1.1     0.00   0.00  83.47     OK
5  r-devel-windows-x86_64-gcc10-UCRT   1.1.1     0.00   0.00   0.00     OK
6             r-patched-linux-x86_64   1.1.1     7.55  49.01  56.56     OK
7              r-patched-solaris-x86   1.1.1     0.00   0.00  89.80     OK
8             r-release-linux-x86_64   1.1.1     7.10  48.80  55.90     OK
9             r-release-macos-x86_64   1.1.1     0.00   0.00   0.00     OK
10             r-oldrel-macos-x86_64   1.1.1     0.00   0.00   0.00     OK
11      r-oldrel-windows-ix86+x86_64   1.1.1     8.00  60.00  68.00     OK
                                                                                     check_url
1  https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/rhub-00check.html
2    https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html
3  https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html
4    https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html
5  https://www.R-project.org/nosvn/R.check/r-devel-windows-x86_64-gcc10-UCRT/rhub-00check.html
6             https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html
7              https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html
8             https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html
9             https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html
10             https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/rhub-00check.html
11      https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/rhub-00check.html

$data$check_details
NULL

Packages by name (history)

Get checks history by package name.

GET [/pkgs] Default limit of 10, max of 50.

GET [/pkgs/{package}/history]

curl https://cranchecks.info/pkgs/rhub/history | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 28338
date: Mon, 15 Mar 2021 12:59:41 GMT

{
    "error": null,
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                        "tinstall": 5.99,
                        "tcheck": 39.3,
                        "ttotal": 45.29,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/rhub-00check.html"
                    },
                    {
                        "flavor": "r-devel-linux-x86_64-fedora-clang",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 78.08,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/rhub-00check.html"
                    },
                    {
                        "flavor": "r-devel-linux-x86_64-fedora-gcc",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 83.46,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/rhub-00check.html"
                    },
                    {
                        "flavor": "r-devel-windows-ix86+x86_64",
                        "version": "1.1.1",
                        "tinstall": 14,
                        "tcheck": 55,
                        "ttotal": 69,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-patched-linux-x86_64",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 0,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-patched-solaris-x86",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 100.4,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/rhub-00check.html"
                    },
                    {
                        "flavor": "r-release-linux-x86_64",
                        "version": "1.1.1",
                        "tinstall": 6.04,
                        "tcheck": 48.7,
                        "ttotal": 54.74,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-release-macos-x86_64",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 0,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-release-windows-ix86+x86_64",
                        "version": "1.1.1",
                        "tinstall": 12,
                        "tcheck": 55,
                        "ttotal": 67,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-oldrel-macos-x86_64",
                        "version": "1.1.1",
                        "tinstall": 0,
                        "tcheck": 0,
                        "ttotal": 0,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/rhub-00check.html"
                    },
                    {
                        "flavor": "r-oldrel-windows-ix86+x86_64",
                        "version": "1.1.1",
                        "tinstall": 8,
                        "tcheck": 52,
                        "ttotal": 60,
                        "status": "OK",
                        "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/rhub-00check.html"
                    }
                ],
                "check_details": null
            }
        ]
    }
}
cchecks::cch_pkgs_history(x = "rhub")
$error
NULL

$data
$data$package
[1] "rhub"

$data$history
# A tibble: 30 x 4
   date_updated  summary$any   $ok $note $warn $error $fail checks check_details
   <chr>         <lgl>       <int> <int> <int>  <int> <int> <list> <lgl>        
 1 2021-03-14T1FALSE          11     0     0      0     0 <df[,NA           
 2 2021-03-13T1FALSE          11     0     0      0     0 <df[,NA           
 3 2021-03-12T1FALSE          13     0     0      0     0 <df[,NA           
 4 2021-03-11T1FALSE          13     0     0      0     0 <df[,NA           
 5 2021-03-10T1FALSE          13     0     0      0     0 <df[,NA           
 6 2021-03-09T1FALSE          13     0     0      0     0 <df[,NA           
 7 2021-03-08T1FALSE          13     0     0      0     0 <df[,NA           
 8 2021-03-07T1FALSE          13     0     0      0     0 <df[,NA           
 9 2021-03-06T1FALSE          12     0     0      0     0 <df[,NA           
10 2021-03-05T1FALSE          12     0     0      0     0 <df[,NA           
# … with 20 more rows

For historical data across packages see the history endpoint.

Badges

Get packages based checks to display in your package README for instance.

In a Markdown-based README to add a badge you just need something like ![alt text](https://cranchecks.info/badges/summary/{package}).

You might want the badge to point at either the CRAN results page or the CRAN checks API page i.e. either

[![Worst CRAN checks result for the rhub package](https://cranchecks.info/badges/worst/rhub)](https://cran.r-project.org/web/checks/check_results_rhub.html) to obtain Badges example, worst for the rhub package.

or

[![Worst CRAN checks result for the rhub package](https://cranchecks.info/badges/worst/rhub)](https://cranchecks.info/pkgs/rhub) to obtain Badges example, worst for the rhub package.

Summary badges

Get badge for CRAN checks summary by package name.

GET [/badges/summary/{package_name}]

[![Summary of CRAN checks results for the rhub package](https://cranchecks.info/badges/summary/rhub)](https://cranchecks.info/pkgs/rhub) gives Summary of CRAN checks results for the rhub package.

curl https://cranchecks.info/badges/summary/rhub
HTTP/2 200 
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 15 Mar 2021 13:04:31 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 15 Mar 2021 12:59:31 GMT

<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
  <linearGradient id="b" x2="0" y2="100%">
    <stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
    <stop offset="1" stop-opacity=".1"/>
  </linearGradient>
  <mask id="a">
    <rect width="70" height="20" rx="3" fill="#fff"/>
  </mask>
  <g mask="url(#a)">
    <path fill="#555" d="M0 0h43v20H0z"/>
    <path fill="#4c1" d="M43 0h46.5v20H43z"/>
    <path fill="url(#b)" d="M0 0h70v20H0z"/>
  </g>
  <g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
    <text x="21.5" y="15" fill="#010101" fill-opacity=".3">
      CRAN
    </text>
    <text x="21.5" y="14">
      CRAN
    </text>
    <text x="55.5" y="15" fill="#010101" fill-opacity=".3">
      OK
    </text>
    <text x="55.5" y="14">
      OK
    </text>
  </g>
</svg>

Worst badges

Get badge for CRAN checks worst result by package name. 😰

GET [/badges/worst/{package_name}]

[![Worst CRAN checks results for the rhub package](https://cranchecks.info/badges/summary/rhub)](https://cranchecks.info/pkgs/rhub) gives Worst CRAN checks results for the rhub package.

curl https://cranchecks.info/badges/worst/rhub
HTTP/2 200 
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 15 Mar 2021 13:04:31 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 15 Mar 2021 12:59:31 GMT

<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
  <linearGradient id="b" x2="0" y2="100%">
    <stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
    <stop offset="1" stop-opacity=".1"/>
  </linearGradient>
  <mask id="a">
    <rect width="70" height="20" rx="3" fill="#fff"/>
  </mask>
  <g mask="url(#a)">
    <path fill="#555" d="M0 0h43v20H0z"/>
    <path fill="#4c1" d="M43 0h46.5v20H43z"/>
    <path fill="url(#b)" d="M0 0h70v20H0z"/>
  </g>
  <g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
    <text x="21.5" y="15" fill="#010101" fill-opacity=".3">
      CRAN
    </text>
    <text x="21.5" y="14">
      CRAN
    </text>
    <text x="55.5" y="15" fill="#010101" fill-opacity=".3">
      OK
    </text>
    <text x="55.5" y="14">
      OK
    </text>
  </g>
</svg>

Flavor badges

Get badge for summary of CRAN checks by flavor and package name.

GET [/badges/flavor/{flavor}/{package}]

💡 List of platforms/flavors

[![CRAN checks result on r-devel-linux-x86_64-debian-clang for the rhub package](https://cranchecks.info/badges/flavor/r-devel-linux-x86_64-debian-clang/rhub)](https://cranchecks.info/pkgs/rhub) gives CRAN checks result on r-devel-linux-x86_64-debian-clang for the rhub package.

curl https://cranchecks.info/badges/flavor/r-devel-linux-x86_64-debian-clang/rhub
HTTP/2 200 
cache-control: max-age=300, public
content-type: image/svg+xml; charset=utf-8
expires: Mon, 15 Mar 2021 13:04:31 GMT
server: Caddy
x-content-type-options: nosniff
content-length: 855
date: Mon, 15 Mar 2021 12:59:31 GMT

<?xml version="1.0" encoding="UTF-8"?>
<svg xmlns="http://www.w3.org/2000/svg" width="70" height="20">
  <linearGradient id="b" x2="0" y2="100%">
    <stop offset="0" stop-color="#bbb" stop-opacity=".1"/>
    <stop offset="1" stop-opacity=".1"/>
  </linearGradient>
  <mask id="a">
    <rect width="70" height="20" rx="3" fill="#fff"/>
  </mask>
  <g mask="url(#a)">
    <path fill="#555" d="M0 0h43v20H0z"/>
    <path fill="#4c1" d="M43 0h46.5v20H43z"/>
    <path fill="url(#b)" d="M0 0h70v20H0z"/>
  </g>
  <g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="11">
    <text x="21.5" y="15" fill="#010101" fill-opacity=".3">
      CRAN
    </text>
    <text x="21.5" y="14">
      CRAN
    </text>
    <text x="55.5" y="15" fill="#010101" fill-opacity=".3">
      OK
    </text>
    <text x="55.5" y="14">
      OK
    </text>
  </g>
</svg>

History

The /history/:date route allows GET requests only. The route is intended for fetching compressed new-line delimited JSON for an individual date, where all CRAN checks data across all packages is combined.

Parameter:

:date
should be of the form YYYY-MM-DD, the minimal value is 2018-12-18.

A request to /history/:date leads to a redirect (http status 302) and a returned JSON body with a message telling the user to follow the link in the Location response header in case they aren’t familiar with redirects. The link to follow is a temporary Amazon S3 link to the JSON file for the given date.

One can automatically get the link to the JSON file by following the redirect. You can do this in curl with the -L flag, or in R by using the followlocation curl option like followlocation=1.

An important note is the data in the JSON file is NOT valid JSON as an entire entity. Each line of the file IS valid JSON; called newline delimited JSON (NDJSON). You don’t have to worry about these details if you use cchecks::cch_history(), which takes care of downloading the file and reading in the compressed NDJSON. On the command line, you can do e.g, download the file, save to a .json.gz gzip-compressed file extension, then in the next line decompress the file with gzip, then pipe to jq, and use head to get the first 10 lines

curl -vL https://cranchecks.info/history/2020-04-01 > 2020-04-01.json.gz
gzip -dc 2020-04-01.json.gz | jq . | head -n 2
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed

  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0*   Trying 52.34.4.0:443...
* Connected to cranchecks.info (52.34.4.0) port 443 (#0)

  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0* ALPN, offering h2
* ALPN, offering http/1.1
} [5 bytes data]
* TLSv1.3 (OUT), TLS handshake, Client hello (1):
} [512 bytes data]
* TLSv1.3 (IN), TLS handshake, Server hello (2):
{ [122 bytes data]
* TLSv1.3 (IN), TLS handshake, Encrypted Extensions (8):
{ [15 bytes data]
* TLSv1.3 (IN), TLS handshake, Certificate (11):
{ [2264 bytes data]
* TLSv1.3 (IN), TLS handshake, CERT verify (15):
{ [78 bytes data]
* TLSv1.3 (IN), TLS handshake, Finished (20):
{ [36 bytes data]
* TLSv1.3 (OUT), TLS change cipher, Change cipher spec (1):
} [1 bytes data]
* TLSv1.3 (OUT), TLS handshake, Finished (20):
} [36 bytes data]
* SSL connection using TLSv1.3 / TLS_AES_128_GCM_SHA256
* ALPN, server accepted to use h2
* Server certificate:
*  subject: CN=cranchecks.info
*  start date: Jan 16 16:57:32 2021 GMT
*  expire date: Apr 16 16:57:32 2021 GMT
*  subjectAltName: host "cranchecks.info" matched cert's "cranchecks.info"
*  issuer: C=US; O=Let's Encrypt; CN=R3
*  SSL certificate verify ok.
* Using HTTP2, server supports multi-use
* Connection state changed (HTTP/2 confirmed)
* Copying HTTP/2 data in stream buffer to connection buffer after upgrade: len=0
} [5 bytes data]
* Using Stream ID: 1 (easy handle 0x7fd81b813e00)
} [5 bytes data]
> GET /history/2020-04-01 HTTP/2
> Host: cranchecks.info
> user-agent: curl/7.75.0
> accept: */*
> 
{ [5 bytes data]
* TLSv1.3 (IN), TLS handshake, Newsession Ticket (4):
{ [130 bytes data]
* Connection state changed (MAX_CONCURRENT_STREAMS == 250)!
} [5 bytes data]
< HTTP/2 302 
< access-control-allow-methods: HEAD, GET
< access-control-allow-origin: *
< cache-control: public, must-revalidate, max-age=60
< content-type: application/json; charset=utf8
< location: https://cchecks-history.s3.us-west-2.amazonaws.com/2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210315%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210315T125934Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=34c039eaa119347ee67350d95da50085d386a311842994d9377e2785deee69c2
< server: Caddy
< x-content-type-options: nosniff
< content-length: 101
< date: Mon, 15 Mar 2021 12:59:34 GMT
< 
{ [5 bytes data]
* Ignoring the response-body
{ [101 bytes data]

100   101  100   101    0     0    266      0 --:--:-- --:--:-- --:--:--   265
* Connection #0 to host cranchecks.info left intact
* Issue another request to this URL: 'https://cchecks-history.s3.us-west-2.amazonaws.com/2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210315%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210315T125934Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=34c039eaa119347ee67350d95da50085d386a311842994d9377e2785deee69c2'
*   Trying 52.218.250.33:443...
* Connected to cchecks-history.s3.us-west-2.amazonaws.com (52.218.250.33) port 443 (#1)
* ALPN, offering h2
* ALPN, offering http/1.1
} [5 bytes data]
* TLSv1.3 (OUT), TLS handshake, Client hello (1):
} [512 bytes data]
* TLSv1.3 (IN), TLS handshake, Server hello (2):
{ [91 bytes data]
* TLSv1.2 (IN), TLS handshake, Certificate (11):
{ [3269 bytes data]
* TLSv1.2 (IN), TLS handshake, Server key exchange (12):
{ [333 bytes data]
* TLSv1.2 (IN), TLS handshake, Server finished (14):
{ [4 bytes data]
* TLSv1.2 (OUT), TLS handshake, Client key exchange (16):
} [70 bytes data]
* TLSv1.2 (OUT), TLS change cipher, Change cipher spec (1):
} [1 bytes data]
* TLSv1.2 (OUT), TLS handshake, Finished (20):
} [16 bytes data]
* TLSv1.2 (IN), TLS handshake, Finished (20):
{ [16 bytes data]
* SSL connection using TLSv1.2 / ECDHE-RSA-AES128-GCM-SHA256
* ALPN, server did not agree to a protocol
* Server certificate:
*  subject: C=US; ST=Washington; L=Seattle; O=Amazon.com, Inc.; CN=*.s3-us-west-2.amazonaws.com
*  start date: Jul 30 00:00:00 2020 GMT
*  expire date: Aug  4 12:00:00 2021 GMT
*  subjectAltName: host "cchecks-history.s3.us-west-2.amazonaws.com" matched cert's "*.s3.us-west-2.amazonaws.com"
*  issuer: C=US; O=DigiCert Inc; OU=www.digicert.com; CN=DigiCert Baltimore CA-2 G2
*  SSL certificate verify ok.
} [5 bytes data]
> GET /2020-04-01.json.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIE65F6ZPF3JF7JTA%2F20210315%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20210315T125934Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=34c039eaa119347ee67350d95da50085d386a311842994d9377e2785deee69c2 HTTP/1.1
> Host: cchecks-history.s3.us-west-2.amazonaws.com
> User-Agent: curl/7.75.0
> Accept: */*
> 
{ [5 bytes data]
* Mark bundle as not supporting multiuse
< HTTP/1.1 200 OK
< x-amz-id-2: QjYq3LwSfDTzgMj4orh0RcT4WWs+DUWtCcypCZicp9rOwgoBEKqQ4AO00jLs7wTrJo5gr4X3R1k=
< x-amz-request-id: 4QWFB9Y68MECMNDR
< Date: Mon, 15 Mar 2021 12:59:35 GMT
< Last-Modified: Wed, 01 Apr 2020 16:36:04 GMT
< ETag: "a7d74593672aa52dace5cd9e62db9351"
< Content-Encoding: gzip
< Accept-Ranges: bytes
< Content-Type: application/json
< Content-Length: 5180606
< Server: AmazonS3
< 
{ [5 bytes data]

  3 5059k    3  177k    0     0   171k      0  0:00:29  0:00:01  0:00:28  171k
100 5059k  100 5059k    0     0  3605k      0  0:00:01  0:00:01 --:--:-- 12.8M
* Connection #1 to host cchecks-history.s3.us-west-2.amazonaws.com left intact
{
  "package": "localIV",

⚠️ 💡 For historical data by package refer to the package history endpoint.

cchecks::cch_history("2020-04-01")
# opening file input connection.

 Found 500 records...
 Found 1000 records...
 Found 1500 records...
 Found 2000 records...
 Found 2500 records...
 Found 3000 records...
 Found 3500 records...
 Found 4000 records...
 Found 4500 records...
 Found 5000 records...
 Found 5500 records...
 Found 6000 records...
 Found 6500 records...
 Found 7000 records...
 Found 7500 records...
 Found 8000 records...
 Found 8500 records...
 Found 9000 records...
 Found 9500 records...
 Found 10000 records...
 Found 10500 records...
 Found 11000 records...
 Found 11500 records...
 Found 12000 records...
 Found 12500 records...
 Found 13000 records...
 Found 13500 records...
 Found 14000 records...
 Found 14500 records...
 Found 15000 records...
 Found 15500 records...
 Found 16000 records...
 Found 16327 records...
 Imported 16327 records. Simplifying...

# closing file input connection.
# A tibble: 16,327 x 5
   package  summary            checks              check_details             date_updated 
   <chr>    <chr>              <chr>               <chr>                     <chr>        
 1 localIV  "{\"any\":false,\… "[{\"flavor\":\"r-… "null"                    2020-04-01 1…
 2 di       "{\"any\":false,\… "[{\"flavor\":\"r-… "null"                    2020-04-01 1…
 3 GAR      "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.1\",\"… 2020-04-01 1…
 4 MetABEL  "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"0.2-0\",… 2020-04-01 1…
 5 quantab… "{\"any\":false,\… "[{\"flavor\":\"r-… "null"                    2020-04-01 1…
 6 ChIPtest "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.0\",\"… 2020-04-01 1…
 7 TSF      "{\"any\":false,\… "[{\"flavor\":\"r-… "null"                    2020-04-01 1…
 8 apercu   "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"0.2.4\",… 2020-04-01 1…
 9 SPRT     "{\"any\":true,\"… "[{\"flavor\":\"r-… "{\"version\":\"1.0\",\"… 2020-04-01 1…
10 W2CWM2C  "{\"any\":false,\… "[{\"flavor\":\"r-… "null"                    2020-04-01 1…
# … with 16,317 more rows

Search

Search package history data. This is a full text search ONLY of the output in check_details field.

Function of the cchecks package: cch_pkgs_search()

GET [/search]

Parameters:

q (string)
full text query, e.g, q=memory
package (string)
a package name. limit results to a single package, e.g, package=taxize
one_each (boolean)
if true, return a single result for each package; useful if you want to find out what packages have match a particular query, and don’t care which day that match happened. default: false; e.g., one_each=true
fields (string)
comma separated string with field to return, e.g., fields=package,check_details
limit/offset
see pagination docs. Max of 50.
curl https://cranchecks.info/search?q=memory | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 180620
date: Mon, 15 Mar 2021 13:00:12 GMT

{
    "error": null,
    "count": 1238,
    "returned": 10,
    "data": [
        {
            "package": "clusternor",
            "date_updated": "2021-02-17T15:03:44.000Z",
            "summary": {
                "any": true,
                "ok": 0,
                "note": 10,
                "warn": 0,
                "error": 2,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "0.0-4",
                    "tinstall": 87.58,
                    "tcheck": 35.57,
                    "ttotal": 123.15,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "0.0-4",
                    "tinstall": 59.7,
                    "tcheck": 25.92,
                    "ttotal": 85.62,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 206.61,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 155.19,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 153,
                    "tcheck": 58,
                    "ttotal": 211,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 73.32,
                    "tcheck": 32.63,
                    "ttotal": 105.95,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 152.6,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 74.03,
                    "tcheck": 32.44,
                    "ttotal": 106.47,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 183,
                    "tcheck": 83,
                    "ttotal": 266,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 149,
                    "tcheck": 72,
                    "ttotal": 221,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/clusternor-00check.html"
                }
            ],
            "check_details": {
                "details": [
                    {
                        "version": "0.0-4",
                        "output": "GNU make is a SystemRequirements.",
                        "check": "for GNU extensions in Makefiles",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
                            "r-patched-linux-x86_64",
                            "r-patched-solaris-x86",
                            "r-release-linux-x86_64",
                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [1s/2s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> memory\n  \n  Warning: stack imbalance in '{', 55 then 54\n  Warning: stack imbalance in '<-', 50 then 49\n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  Fatal error: ****snapping into wrong generation",
                        "check": "tests",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-gcc"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  installed size is  7.3Mb\n  sub-directories of 1Mb or more:\n    libs   7.2Mb",
                        "check": "installed package size",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [5s/22s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.651749 1.554835 1.669196 1.823017 1.698992\n  [2,] 1.582700 1.565456 1.712063 1.644104 1.870101\n  [3,] 1.651755 1.554831 1.669235 1.822900 1.699119\n  [4,] 1.585971 1.557177 1.766105 1.665046 1.818082\n  [5,] 1.651741 1.554840 1.669151 1.823152 1.698843\n  [6,] 1.651740 1.554839 1.669146 1.823166 1.698828\n  [7,] 1.651750 1.554834 1.669202 1.822998 1.699012\n  [8,] 1.651711 1.554861 1.668998 1.823611 1.698337\n  \n  $cluster\n   [1] 4 4 4 4 8 8 4 4 8 4 4 8 4 4 4 4 4 4 8 4 4 8 4 4 4 8 4 4 8 4 4 2 2 8 8 4 4 4\n  [39] 4 4 4 8 4 2 8 4 8 4 4 2\n  \n  $size\n  [1]  0  4  0 33  0  0  0 13\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]      [,5]\n  [1,] 1.649158 1.506655 1.712068 1.711550 1.8009668\n  [2,] 1.649642 1.506697 1.711777 1.713693 1.7990922\n  [3,] 1.649705 1.506705 1.711741 1.713967 1.7988480\n  [4,] 1.649686 1.506702 1.711749 1.713894 1.7989162\n  [5,] 1.085162 2.038530 1.079136 2.106897 0.9808955\n  [6,] 1.649685 1.506701 1.711749 1.713891 1.7989196\n  [7,] 1.649647 1.506697 1.711774 1.713714 1.7990740\n  [8,] 1.649792 1.506719 1.711683 1.714379 1.7984872\n  \n  $cluster\n   [1] 1 1 1 1 5 8 1 1 8 1 1 8 8 1 1 8 8 1 8 1 8 8 8 1 1 8 8 1 5 1 1 1 1 5 8 8 1 1\n  [39] 8 1 8 8 1 1 8 1 8 8 1 1\n  \n  $size\n  [1] 27  0  0  0  3  0  0 20\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.888524 2.603497 2.066828 2.375178 4.408128\n  [2,] 2.221906 3.679545 2.487253 2.001356 4.078200\n  [3,] 3.363949 1.514688 3.809288 1.941361 3.547053\n  [4,] 2.513951 3.081818 4.215258 1.409905 3.593325\n  [5,] 1.676915 3.191770 2.080428 4.447292 2.429021\n  [6,] 3.672408 1.905373 2.369369 4.077653 2.867364\n  [7,] 3.815225 4.217887 1.862281 2.514782 2.702868\n  [8,] 3.703079 4.045515 3.700746 3.861883 2.418166\n  \n  $cluster\n   [1] 1 6 3 4 7 4 3 3 2 6 3 8 2 7 6 7 6 7 5 4 5 1 4 8 8 4 4 8 8 5 1 6 8 2 7 8 6 8\n  [39] 1 8 7 8 5 8 2 8 6 8 5 8\n  \n  $size\n  [1]  4  4  4  6  5  7  6 14\n ",
                        "check": "tests",
                        "flavors": [
                            "r-patched-solaris-x86"
                        ]
                    }
                ],
                "additional_issues": null
            }
        },
        {
            "package": "clusternor",
            "date_updated": "2021-02-23T15:03:48.000Z",
            "summary": {
                "any": true,
                "ok": 0,
                "note": 10,
                "warn": 0,
                "error": 2,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "0.0-4",
                    "tinstall": 90.11,
                    "tcheck": 35.4,
                    "ttotal": 125.51,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "0.0-4",
                    "tinstall": 59.62,
                    "tcheck": 26.08,
                    "ttotal": 85.7,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 207.18,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 156.15,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 153,
                    "tcheck": 58,
                    "ttotal": 211,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 72.33,
                    "tcheck": 32.6,
                    "ttotal": 104.93,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 152.6,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 72.46,
                    "tcheck": 33.01,
                    "ttotal": 105.47,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 183,
                    "tcheck": 83,
                    "ttotal": 266,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 149,
                    "tcheck": 72,
                    "ttotal": 221,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/clusternor-00check.html"
                }
            ],
            "check_details": {
                "details": [
                    {
                        "version": "0.0-4",
                        "output": "GNU make is a SystemRequirements.",
                        "check": "for GNU extensions in Makefiles",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
                            "r-patched-linux-x86_64",
                            "r-patched-solaris-x86",
                            "r-release-linux-x86_64",
                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [1s/2s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Warning: stack imbalance in '{', 55 then 54\n  Warning: stack imbalance in '<-', 50 then 49\n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  Fatal error: *** recursive gc invocation",
                        "check": "tests",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-gcc"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  installed size is  7.3Mb\n  sub-directories of 1Mb or more:\n    libs   7.2Mb",
                        "check": "installed package size",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [5s/22s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.651749 1.554835 1.669196 1.823017 1.698992\n  [2,] 1.582700 1.565456 1.712063 1.644104 1.870101\n  [3,] 1.651755 1.554831 1.669235 1.822900 1.699119\n  [4,] 1.585971 1.557177 1.766105 1.665046 1.818082\n  [5,] 1.651741 1.554840 1.669151 1.823152 1.698843\n  [6,] 1.651740 1.554839 1.669146 1.823166 1.698828\n  [7,] 1.651750 1.554834 1.669202 1.822998 1.699012\n  [8,] 1.651711 1.554861 1.668998 1.823611 1.698337\n  \n  $cluster\n   [1] 4 4 4 4 8 8 4 4 8 4 4 8 4 4 4 4 4 4 8 4 4 8 4 4 4 8 4 4 8 4 4 2 2 8 8 4 4 4\n  [39] 4 4 4 8 4 2 8 4 8 4 4 2\n  \n  $size\n  [1]  0  4  0 33  0  0  0 13\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]      [,5]\n  [1,] 1.649158 1.506655 1.712068 1.711550 1.8009668\n  [2,] 1.649642 1.506697 1.711777 1.713693 1.7990922\n  [3,] 1.649705 1.506705 1.711741 1.713967 1.7988480\n  [4,] 1.649686 1.506702 1.711749 1.713894 1.7989162\n  [5,] 1.085162 2.038530 1.079136 2.106897 0.9808955\n  [6,] 1.649685 1.506701 1.711749 1.713891 1.7989196\n  [7,] 1.649647 1.506697 1.711774 1.713714 1.7990740\n  [8,] 1.649792 1.506719 1.711683 1.714379 1.7984872\n  \n  $cluster\n   [1] 1 1 1 1 5 8 1 1 8 1 1 8 8 1 1 8 8 1 8 1 8 8 8 1 1 8 8 1 5 1 1 1 1 5 8 8 1 1\n  [39] 8 1 8 8 1 1 8 1 8 8 1 1\n  \n  $size\n  [1] 27  0  0  0  3  0  0 20\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.888524 2.603497 2.066828 2.375178 4.408128\n  [2,] 2.221906 3.679545 2.487253 2.001356 4.078200\n  [3,] 3.363949 1.514688 3.809288 1.941361 3.547053\n  [4,] 2.513951 3.081818 4.215258 1.409905 3.593325\n  [5,] 1.676915 3.191770 2.080428 4.447292 2.429021\n  [6,] 3.672408 1.905373 2.369369 4.077653 2.867364\n  [7,] 3.815225 4.217887 1.862281 2.514782 2.702868\n  [8,] 3.703079 4.045515 3.700746 3.861883 2.418166\n  \n  $cluster\n   [1] 1 6 3 4 7 4 3 3 2 6 3 8 2 7 6 7 6 7 5 4 5 1 4 8 8 4 4 8 8 5 1 6 8 2 7 8 6 8\n  [39] 1 8 7 8 5 8 2 8 6 8 5 8\n  \n  $size\n  [1]  4  4  4  6  5  7  6 14\n ",
                        "check": "tests",
                        "flavors": [
                            "r-patched-solaris-x86"
                        ]
                    }
                ],
                "additional_issues": null
            }
        },
        {
            "package": "clusternor",
            "date_updated": "2021-02-26T15:03:50.000Z",
            "summary": {
                "any": true,
                "ok": 0,
                "note": 10,
                "warn": 0,
                "error": 2,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "0.0-4",
                    "tinstall": 86.91,
                    "tcheck": 34.97,
                    "ttotal": 121.88,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "0.0-4",
                    "tinstall": 59.99,
                    "tcheck": 26.32,
                    "ttotal": 86.31,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 207.18,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 156.15,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/clusternor-00check.html"
                },
                {
                    "flavor": "r-devel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 153,
                    "tcheck": 58,
                    "ttotal": 211,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 73.64,
                    "tcheck": 32.75,
                    "ttotal": 106.39,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 152.6,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "0.0-4",
                    "tinstall": 71.68,
                    "tcheck": 32.53,
                    "ttotal": 104.21,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-release-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 183,
                    "tcheck": 83,
                    "ttotal": 266,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "0.0-4",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/clusternor-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "0.0-4",
                    "tinstall": 149,
                    "tcheck": 72,
                    "ttotal": 221,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/clusternor-00check.html"
                }
            ],
            "check_details": {
                "details": [
                    {
                        "version": "0.0-4",
                        "output": "GNU make is a SystemRequirements.",
                        "check": "for GNU extensions in Makefiles",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
                            "r-patched-linux-x86_64",
                            "r-patched-solaris-x86",
                            "r-release-linux-x86_64",
                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [1s/2s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> memory\n  \n  Warning: stack imbalance in '{', 55 then 56\n  Warning: stack imbalance in '<-', 50 then 51\n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 3.064769 2.934908 2.738242 3.298497 2.844551\n  [2,] 3.015320 3.013633 2.770685 2.955266 3.051938\n  [3,] 4.513284 3.880610 4.156640 4.325825 3.100727\n  [4,] 2.849448 2.974869 2.946936 2.447302 3.327008\n  [5,] 2.491785 2.790580 3.414452 1.913792 3.267746\n  [6,] 3.096226 2.912256 2.765275 3.344278 2.809726\n  [7,] 2.887287 3.006538 2.990962 2.472479 3.301115\n  [8,] 3.248763 4.155510 1.973610 3.654074 2.660320\n  \n  $cluster\n   [1] 2 1 5 5 8 5 5 4 4 6 7 8 5 8 6 2 6 7 8 5 8 5 5 3 5 5 5 2 3 1 4 6 6 8 8 5 1 3\n  [39] 4 3 8 3 8 3 5 8 3 3 6 3\n  \n  $size\n  [1]  3  3  9  4 13  6  2 10\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.977810 2.870101 3.038839 3.304946 3.270245\n  [2,] 2.977707 2.870096 3.038940 3.304566 3.270613\n  [3,] 2.977625 2.870094 3.039058 3.304200 3.270973\n  [4,] 2.977839 2.870101 3.038744 3.305169 3.270018\n  [5,] 2.977842 2.870101 3.038733 3.305195 3.269992\n  [6,] 2.977807 2.870099 3.038780 3.305043 3.270142\n  [7,] 2.977696 2.870096 3.038949 3.304530 3.270648\n  [8,] 2.977984 2.870108 3.038509 3.305866 3.269326\n  \n  $cluster\n   [1] 3 3 3 3 8 8 3 3 8 3 3 8 8 3 8 8 8 3 8 3 8 8 8 3 3 8 8 3 8 3 3 3 3 8 8 8 3 3\n  [39] 8 3 8 8 3 3 8 8 8 8 3 3\n  \n  $size\n  [1]  0  0 25  0  0  0  0 25\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  Fatal error: *** recursive gc invocation",
                        "check": "tests",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-gcc"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  installed size is  7.3Mb\n  sub-directories of 1Mb or more:\n    libs   7.2Mb",
                        "check": "installed package size",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
                        ]
                    },
                    {
                        "version": "0.0-4",
                        "output": "  Running ‘testthat.R’ [5s/22s]\nRunning the tests in ‘tests/testthat.R’ failed.\nComplete output:\n  > library(testthat)\n  > library(clusternor)\n  Loading required package: Rcpp\n  > \n  > test_check(\"clusternor\")\n  \n  \n  ***Running test for fcmeans***\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> memory\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> memory, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 17\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [2,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [3,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [4,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [5,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [6,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  [7,] 1.944158 1.873933 1.811169 1.829127 1.705402\n  [8,] 1.944158 1.873933 1.811169 1.829127 1.705401\n  \n  $cluster\n   [1] 7 3 7 7 3 7 7 7 7 3 7 3 7 3 3 7 3 7 3 7 3 7 7 3 3 7 7 3 3 3 7 3 3 7 3 7 3 3\n  [39] 7 3 3 3 3 3 7 3 3 3 3 3\n  \n  $size\n  [1]  0  0 29  0  0  0 21  0\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 1.651749 1.554835 1.669196 1.823017 1.698992\n  [2,] 1.582700 1.565456 1.712063 1.644104 1.870101\n  [3,] 1.651755 1.554831 1.669235 1.822900 1.699119\n  [4,] 1.585971 1.557177 1.766105 1.665046 1.818082\n  [5,] 1.651741 1.554840 1.669151 1.823152 1.698843\n  [6,] 1.651740 1.554839 1.669146 1.823166 1.698828\n  [7,] 1.651750 1.554834 1.669202 1.822998 1.699012\n  [8,] 1.651711 1.554861 1.668998 1.823611 1.698337\n  \n  $cluster\n   [1] 4 4 4 4 8 8 4 4 8 4 4 8 4 4 4 4 4 4 8 4 4 8 4 4 4 8 4 4 8 4 4 2 2 8 8 4 4 4\n  [39] 4 4 4 8 4 2 8 4 8 4 4 2\n  \n  $size\n  [1]  0  4  0 33  0  0  0 13\n  \n  Data ==> disk, centroids ==> compute\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 21\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]      [,5]\n  [1,] 1.649158 1.506655 1.712068 1.711550 1.8009668\n  [2,] 1.649642 1.506697 1.711777 1.713693 1.7990922\n  [3,] 1.649705 1.506705 1.711741 1.713967 1.7988480\n  [4,] 1.649686 1.506702 1.711749 1.713894 1.7989162\n  [5,] 1.085162 2.038530 1.079136 2.106897 0.9808955\n  [6,] 1.649685 1.506701 1.711749 1.713891 1.7989196\n  [7,] 1.649647 1.506697 1.711774 1.713714 1.7990740\n  [8,] 1.649792 1.506719 1.711683 1.714379 1.7984872\n  \n  $cluster\n   [1] 1 1 1 1 5 8 1 1 8 1 1 8 8 1 1 8 8 1 8 1 8 8 8 1 1 8 8 1 5 1 1 1 1 5 8 8 1 1\n  [39] 8 1 8 8 1 1 8 1 8 8 1 1\n  \n  $size\n  [1] 27  0  0  0  3  0  0 20\n  \n  \n  \n  ***Running test for hmeans***\n  \n  Data ==>  ,centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.426766 2.953499 4.043335 2.244559 3.710492\n  [2,] 4.122332 2.465384 3.589322 2.166748 3.575502\n  [3,] 2.626000 3.584148 2.022466 2.295955 4.134119\n  [4,] 1.943198 1.376050 2.189751 3.513497 4.592882\n  [5,] 4.307359 2.781234 3.196755 4.311270 3.415023\n  [6,] 2.795000 3.228041 4.430282 4.288907 1.526741\n  [7,] 1.580627 3.095462 1.962946 4.057300 1.642651\n  [8,] 2.477416 2.417114 2.200970 4.737974 2.761689\n  \n  $cluster\n   [1] 5 1 3 2 7 8 1 1 8 1 4 7 6 1 5 5 5 1 5 2 6 5 2 3 4 5 1 2 7 3 3 4 3 7 5 8 1 1\n  [39] 6 5 5 6 2 3 7 3 5 7 2 3\n  \n  $size\n  [1]  9  6  8  3 11  4  6  3\n  \n  Data ==> memory, centroids ==> memory\n  \n  $nrow\n  [1] 50\n  \n  $ncol\n  [1] 5\n  \n  $iters\n  [1] 20\n  \n  $k\n  [1] 8\n  \n  $centers\n           [,1]     [,2]     [,3]     [,4]     [,5]\n  [1,] 2.888524 2.603497 2.066828 2.375178 4.408128\n  [2,] 2.221906 3.679545 2.487253 2.001356 4.078200\n  [3,] 3.363949 1.514688 3.809288 1.941361 3.547053\n  [4,] 2.513951 3.081818 4.215258 1.409905 3.593325\n  [5,] 1.676915 3.191770 2.080428 4.447292 2.429021\n  [6,] 3.672408 1.905373 2.369369 4.077653 2.867364\n  [7,] 3.815225 4.217887 1.862281 2.514782 2.702868\n  [8,] 3.703079 4.045515 3.700746 3.861883 2.418166\n  \n  $cluster\n   [1] 1 6 3 4 7 4 3 3 2 6 3 8 2 7 6 7 6 7 5 4 5 1 4 8 8 4 4 8 8 5 1 6 8 2 7 8 6 8\n  [39] 1 8 7 8 5 8 2 8 6 8 5 8\n  \n  $size\n  [1]  4  4  4  6  5  7  6 14\n ",
                        "check": "tests",
                        "flavors": [
                            "r-patched-solaris-x86"
                        ]
                    }
                ],
                "additional_issues": null
            }
        },
        {
            "package": "allan",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": {
                "any": true,
                "ok": 0,
                "note": 9,
                "warn": 0,
                "error": 3,
                "fail": 0
            },
            "checks": [
                {
                    "flavor": "r-devel-linux-x86_64-debian-clang",
                    "version": "1.01",
                    "tinstall": 3.09,
                    "tcheck": 35.96,
                    "ttotal": 39.05,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/allan-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-debian-gcc",
                    "version": "1.01",
                    "tinstall": 2.16,
                    "tcheck": 28.08,
                    "ttotal": 30.24,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/allan-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-clang",
                    "version": "1.01",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 55.43,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-clang/allan-00check.html"
                },
                {
                    "flavor": "r-devel-linux-x86_64-fedora-gcc",
                    "version": "1.01",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 46.06,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-linux-x86_64-fedora-gcc/allan-00check.html"
                },
                {
                    "flavor": "r-devel-windows-ix86+x86_64",
                    "version": "1.01",
                    "tinstall": 6,
                    "tcheck": 59,
                    "ttotal": 65,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-devel-windows-ix86+x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-patched-linux-x86_64",
                    "version": "1.01",
                    "tinstall": 2.75,
                    "tcheck": 34.65,
                    "ttotal": 37.4,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-linux-x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-patched-solaris-x86",
                    "version": "1.01",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 71.7,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-patched-solaris-x86/allan-00check.html"
                },
                {
                    "flavor": "r-release-linux-x86_64",
                    "version": "1.01",
                    "tinstall": 2.72,
                    "tcheck": 34.5,
                    "ttotal": 37.22,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-linux-x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-release-macos-x86_64",
                    "version": "1.01",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-macos-x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-release-windows-ix86+x86_64",
                    "version": "1.01",
                    "tinstall": 16,
                    "tcheck": 64,
                    "ttotal": 80,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-release-windows-ix86+x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-oldrel-macos-x86_64",
                    "version": "1.01",
                    "tinstall": 0,
                    "tcheck": 0,
                    "ttotal": 0,
                    "status": "NOTE",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-macos-x86_64/allan-00check.html"
                },
                {
                    "flavor": "r-oldrel-windows-ix86+x86_64",
                    "version": "1.01",
                    "tinstall": 4,
                    "tcheck": 44,
                    "ttotal": 48,
                    "status": "ERROR",
                    "check_url": "https://www.R-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/allan-00check.html"
                }
            ],
            "check_details": {
                "details": [
                    {
                        "version": "1.01",
                        "output": "Malformed Description field: should contain one or more complete sentences.",
                        "check": "DESCRIPTION meta-information",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
                            "r-patched-linux-x86_64",
                            "r-patched-solaris-x86",
                            "r-release-linux-x86_64",
                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "allanVarSelect: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'update'\ngetbestchunksize: no visible global function definition for 'read.csv'\ngetbestchunksize: no visible global function definition for\n  'object.size'\npredictvbiglm: no visible global function definition for 'read.csv'\npredictvbiglm: no visible global function definition for 'predict'\npredictvbiglm: no visible global function definition for\n  'weighted.mean'\nreadinbigdata : <anonymous>: no visible global function definition for\n  'read.csv'\nUndefined global functions or variables:\n  object.size predict read.csv update weighted.mean\nConsider adding\n  importFrom(\"stats\", \"predict\", \"update\", \"weighted.mean\")\n  importFrom(\"utils\", \"object.size\", \"read.csv\")\nto your NAMESPACE file.",
                        "check": "R code for possible problems",
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                            "r-devel-linux-x86_64-fedora-gcc",
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                            "r-patched-solaris-x86",
                            "r-release-linux-x86_64",
                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "prepare_Rd: allan-package.Rd:49-51: Dropping empty section \\seealso\nprepare_Rd: allanVarSelect.Rd:59-60: Dropping empty section \\details\nprepare_Rd: allanVarSelect.Rd:66-67: Dropping empty section \\references\nprepare_Rd: allanVarSelect.Rd:78-79: Dropping empty section \\seealso\nprepare_Rd: fitvbiglm.Rd:38-39: Dropping empty section \\details\nprepare_Rd: fitvbiglm.Rd:49-50: Dropping empty section \\note\nprepare_Rd: fitvbiglm.Rd:43-44: Dropping empty section \\references\nprepare_Rd: fitvbiglm.Rd:53-54: Dropping empty section \\seealso\nprepare_Rd: getbestchunksize.Rd:35-36: Dropping empty section \\details\nprepare_Rd: getbestchunksize.Rd:46-47: Dropping empty section \\note\nprepare_Rd: getbestchunksize.Rd:40-41: Dropping empty section \\references\nprepare_Rd: getbestchunksize.Rd:50-51: Dropping empty section \\seealso\nprepare_Rd: predictvbiglm.Rd:44-45: Dropping empty section \\details\nprepare_Rd: predictvbiglm.Rd:56-57: Dropping empty section \\note\nprepare_Rd: predictvbiglm.Rd:50-51: Dropping empty section \\references\nprepare_Rd: predictvbiglm.Rd:60-61: Dropping empty section \\seealso\nprepare_Rd: readinbigdata.Rd:42-43: Dropping empty section \\note\nprepare_Rd: readinbigdata.Rd:45-46: Dropping empty section \\seealso",
                        "check": "Rd files",
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                            "r-oldrel-windows-ix86+x86_64"
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                    {
                        "version": "1.01",
                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
                        "check": "Rd line widths",
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                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-patched-linux-x86_64",
                            "r-release-linux-x86_64"
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                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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                        "output": "allanVarSelect: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'update'\ngetbestchunksize: no visible global function definition for 'read.csv'\ngetbestchunksize: no visible global function definition for\n  'object.size'\npredictvbiglm: no visible global function definition for 'read.csv'\npredictvbiglm: no visible global function definition for 'predict'\npredictvbiglm: no visible global function definition for\n  'weighted.mean'\nreadinbigdata : <anonymous>: no visible global function definition for\n  'read.csv'\nUndefined global functions or variables:\n  object.size predict read.csv update weighted.mean\nConsider adding\n  importFrom(\"stats\", \"predict\", \"update\", \"weighted.mean\")\n  importFrom(\"utils\", \"object.size\", \"read.csv\")\nto your NAMESPACE file.",
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                        "output": "prepare_Rd: allan-package.Rd:49-51: Dropping empty section \\seealso\nprepare_Rd: allanVarSelect.Rd:59-60: Dropping empty section \\details\nprepare_Rd: allanVarSelect.Rd:66-67: Dropping empty section \\references\nprepare_Rd: allanVarSelect.Rd:78-79: Dropping empty section \\seealso\nprepare_Rd: fitvbiglm.Rd:38-39: Dropping empty section \\details\nprepare_Rd: fitvbiglm.Rd:49-50: Dropping empty section \\note\nprepare_Rd: fitvbiglm.Rd:43-44: Dropping empty section \\references\nprepare_Rd: fitvbiglm.Rd:53-54: Dropping empty section \\seealso\nprepare_Rd: getbestchunksize.Rd:35-36: Dropping empty section \\details\nprepare_Rd: getbestchunksize.Rd:46-47: Dropping empty section \\note\nprepare_Rd: getbestchunksize.Rd:40-41: Dropping empty section \\references\nprepare_Rd: getbestchunksize.Rd:50-51: Dropping empty section \\seealso\nprepare_Rd: predictvbiglm.Rd:44-45: Dropping empty section \\details\nprepare_Rd: predictvbiglm.Rd:56-57: Dropping empty section \\note\nprepare_Rd: predictvbiglm.Rd:50-51: Dropping empty section \\references\nprepare_Rd: predictvbiglm.Rd:60-61: Dropping empty section \\seealso\nprepare_Rd: readinbigdata.Rd:42-43: Dropping empty section \\note\nprepare_Rd: readinbigdata.Rd:45-46: Dropping empty section \\seealso",
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                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
                        "check": "Rd line widths",
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                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-patched-linux-x86_64",
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "output": "allanVarSelect: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'update'\ngetbestchunksize: no visible global function definition for 'read.csv'\ngetbestchunksize: no visible global function definition for\n  'object.size'\npredictvbiglm: no visible global function definition for 'read.csv'\npredictvbiglm: no visible global function definition for 'predict'\npredictvbiglm: no visible global function definition for\n  'weighted.mean'\nreadinbigdata : <anonymous>: no visible global function definition for\n  'read.csv'\nUndefined global functions or variables:\n  object.size predict read.csv update weighted.mean\nConsider adding\n  importFrom(\"stats\", \"predict\", \"update\", \"weighted.mean\")\n  importFrom(\"utils\", \"object.size\", \"read.csv\")\nto your NAMESPACE file.",
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                        "version": "1.01",
                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
                        "check": "Rd line widths",
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                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-patched-linux-x86_64",
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
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                    {
                        "version": "1.01",
                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
                        "check": "Rd line widths",
                        "flavors": [
                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-patched-linux-x86_64",
                            "r-release-linux-x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
                            "r-devel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
                            "r-release-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
                            "r-oldrel-windows-ix86+x86_64"
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                "additional_issues": null
            }
        }
    ]
}
cchecks::cch_pkgs_search(q = "memory")
$error
NULL

$count
[1] 1238

$returned
[1] 30

$data
# A tibble: 30 x 5
   package  date_updated     summary$any   $ok $note $warn $error $fail checks  
   <chr>    <chr>            <lgl>       <int> <int> <int>  <int> <int> <list>  
 1 cluster2021-02-17T15:0TRUE            0    10     0      2     0 <df[,7]2 cluster2021-02-23T15:0TRUE            0    10     0      2     0 <df[,7]3 cluster2021-02-26T15:0TRUE            0    10     0      2     0 <df[,7]4 allan    2021-02-13T15:0TRUE            0     9     0      3     0 <df[,7]5 allan    2021-02-14T15:0TRUE            0     9     0      3     0 <df[,7]6 allan    2021-02-15T15:0TRUE            0     9     0      3     0 <df[,7]7 allan    2021-02-16T15:0TRUE            0     9     0      3     0 <df[,7]8 allan    2021-02-17T15:0TRUE            0     9     0      3     0 <df[,7]9 allan    2021-02-18T15:0TRUE            0     9     0      3     0 <df[,7]10 allan    2021-02-19T15:0TRUE            0     9     0      3     0 <df[,7]# … with 20 more rows, and 1 more variable: check_details <df[,2]>

curl https://cranchecks.info/search?q=memory&one_each=true&limit=2 | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 32612
date: Mon, 15 Mar 2021 13:00:34 GMT

{
    "error": null,
    "count": 58,
    "returned": 2,
    "data": [
        {
            "package": "allan",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": {
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            "check_details": {
                "details": [
                    {
                        "version": "1.01",
                        "output": "Malformed Description field: should contain one or more complete sentences.",
                        "check": "DESCRIPTION meta-information",
                        "flavors": [
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                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
                            "r-patched-linux-x86_64",
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                            "r-release-macos-x86_64",
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                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "allanVarSelect: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'read.csv'\nfitvbiglm: no visible global function definition for 'update'\ngetbestchunksize: no visible global function definition for 'read.csv'\ngetbestchunksize: no visible global function definition for\n  'object.size'\npredictvbiglm: no visible global function definition for 'read.csv'\npredictvbiglm: no visible global function definition for 'predict'\npredictvbiglm: no visible global function definition for\n  'weighted.mean'\nreadinbigdata : <anonymous>: no visible global function definition for\n  'read.csv'\nUndefined global functions or variables:\n  object.size predict read.csv update weighted.mean\nConsider adding\n  importFrom(\"stats\", \"predict\", \"update\", \"weighted.mean\")\n  importFrom(\"utils\", \"object.size\", \"read.csv\")\nto your NAMESPACE file.",
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                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-devel-windows-ix86+x86_64",
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                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
                    },
                    {
                        "version": "1.01",
                        "output": "prepare_Rd: allan-package.Rd:49-51: Dropping empty section \\seealso\nprepare_Rd: allanVarSelect.Rd:59-60: Dropping empty section \\details\nprepare_Rd: allanVarSelect.Rd:66-67: Dropping empty section \\references\nprepare_Rd: allanVarSelect.Rd:78-79: Dropping empty section \\seealso\nprepare_Rd: fitvbiglm.Rd:38-39: Dropping empty section \\details\nprepare_Rd: fitvbiglm.Rd:49-50: Dropping empty section \\note\nprepare_Rd: fitvbiglm.Rd:43-44: Dropping empty section \\references\nprepare_Rd: fitvbiglm.Rd:53-54: Dropping empty section \\seealso\nprepare_Rd: getbestchunksize.Rd:35-36: Dropping empty section \\details\nprepare_Rd: getbestchunksize.Rd:46-47: Dropping empty section \\note\nprepare_Rd: getbestchunksize.Rd:40-41: Dropping empty section \\references\nprepare_Rd: getbestchunksize.Rd:50-51: Dropping empty section \\seealso\nprepare_Rd: predictvbiglm.Rd:44-45: Dropping empty section \\details\nprepare_Rd: predictvbiglm.Rd:56-57: Dropping empty section \\note\nprepare_Rd: predictvbiglm.Rd:50-51: Dropping empty section \\references\nprepare_Rd: predictvbiglm.Rd:60-61: Dropping empty section \\seealso\nprepare_Rd: readinbigdata.Rd:42-43: Dropping empty section \\note\nprepare_Rd: readinbigdata.Rd:45-46: Dropping empty section \\seealso",
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                            "r-release-macos-x86_64",
                            "r-release-windows-ix86+x86_64",
                            "r-oldrel-macos-x86_64",
                            "r-oldrel-windows-ix86+x86_64"
                        ]
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                    {
                        "version": "1.01",
                        "output": "Rd file 'allan-package.Rd':\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=smallchunk,weights=~cont0)\n\nRd file 'allanVarSelect.Rd':\n  \\usage lines wider than 90 characters:\n     allanVarSelect(BaseModel, TrnDataSetFile, ValDataSetFile, ResponseCol = 1, NumOfSteps = 10, criteria = \"AIC\", currentchunksize = -1, si ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'fitvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n\nRd file 'getbestchunksize.Rd':\n  \\usage lines wider than 90 characters:\n     getbestchunksize(filename, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095, silent = TRUE)\n  \\examples lines wider than 100 characters:\n             #This is done by reading in a number of rows(1000 by default)and then measuring the size of the memory\n             #used.  Memory allwed is specified in Gb.  The adjfactor is a factor used to adjust memory for overhead\n\nRd file 'predictvbiglm.Rd':\n  \\usage lines wider than 90 characters:\n     predictvbiglm(BaseModel, ValFileName, currentchunksize = -1, ResponseCol = 1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, Ad ... [TRUNCATED]\n  \\examples lines wider than 100 characters:\n     bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n     predictvbiglm<-function(BaseModel,ValFileName,currentchunksize=-1,ResponseCol=1,silent=TRUE,MemoryAllowed=0.5,TestedRows=1000,AdjFactor ... [TRUNCATED]\n                     currentchunksize<-getbestchunksize(ValFileName,MemoryAllowed=MemoryAllowed,TestedRows=TestedRows,AdjFactor=AdjFactor,si ... [TRUNCATED]\n                             weightvector<-as.vector(eval(parse(text=paste(\"CurrentDataSet\",\"$\",weightname,sep=\"\"))))\n                     CurrentVariance=sum(((CurrentDataSet[,ResponseCol]-CurrentMean)^2)*weightvector)/sum(weightvector)\n\nRd file 'readinbigdata.Rd':\n  \\examples lines wider than 100 characters:\n             #The return value is either the next chunk of data or NULL if there is no additional data left.\n             #Additionally if a reset=TRUE flag is passed, then the data stream goes back to the beginning.\n\nThese lines will be truncated in the PDF manual.",
                        "check": "Rd line widths",
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                            "r-devel-linux-x86_64-debian-clang",
                            "r-devel-linux-x86_64-debian-gcc",
                            "r-devel-linux-x86_64-fedora-clang",
                            "r-devel-linux-x86_64-fedora-gcc",
                            "r-patched-linux-x86_64",
                            "r-release-linux-x86_64"
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                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpukHfZE/RLIBS_c44c28153910/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
                            "r-devel-windows-ix86+x86_64"
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                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpEHUBR4/RLIBS_12fec2e8ba2c/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
                        "flavors": [
                            "r-release-windows-ix86+x86_64"
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                    },
                    {
                        "version": "1.01",
                        "output": "Running examples in 'allan-Ex.R' failed\nThe error most likely occurred in:\n\n> ### Name: allanVarSelect\n> ### Title: Memory Unlimited Forward Stepwise Variable Selection for Linear\n> ###   Models\n> ### Aliases: allanVarSelect\n> ### Keywords: stepwise linear regression memory\n> \n> ### ** Examples\n> \n> #Get external data.  For your own data skip this next line and replace all\n> #instance of SampleData with \"YourFile.csv\".\n> SampleData=system.file(\"extdata\",\"SampleDataFile.csv\", package = \"allan\")\n> \n> #fit smaller data to biglm object\n> columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))\n> datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)\n> datafeed(TRUE)\n> firstchunk<-datafeed(FALSE)\n> \n> #create a biglm model from the small chunk with all variables that will be consdered\n> #for variable selection.\n> bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)\n> \n> #now run variable selection\n> FinalModel<-allanVarSelect(bigmodel,SampleData,SampleData,NumOfSteps=2,criteria=\"MSE\",silent=FALSE)\n[1] \"Total memory usage for 1000 lines:\"\n110560 bytes\n[1] \"Chunksize for dataframe after adjustment factor:\"\n[1] 429630\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529253.65122942\"      \"1529265.34987705\" \"1.29997019294336e+129\" \n                                                \n                \"cont3\"                     \"1\" \n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Iterating Through Dataset and Updating Coefficients\"\n[1] \"Criteria:MSE\"\n[1] \"Iteration Result\"\n               AICValue                BICValue                MSEValue \n     \"1529255.65122942\"      \"1529273.19920087\" \"1.29902541076004e+129\" \n                                                \n                \"cont1\"                     \"2\" \n[1] \"Final Results of Variable Selection:\"\n                 AICValue           BICValue           MSEValue               \nIterationSummary \"1529253.65122942\" \"1529265.34987705\" \"1.29997019294336e+129\"\nIterationSummary \"1529255.65122942\" \"1529273.19920087\" \"1.29902541076004e+129\"\n                            \nIterationSummary \"cont3\" \"1\"\nIterationSummary \"cont1\" \"2\"\n[1] \"Results Stored in $SelectionSummary\"\n> \n> \n> \n> \n> \n> \n> \n> cleanEx()\nWarning in .Internal(gc(verbose, reset, full)) :\n  closing unused connection 3 (D:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv)\nError: connections left open:\n\tD:/temp/RtmpE9PIOK/RLIBS_eb3860833110/allan/extdata/SampleDataFile.csv (file)\nExecution halted",
                        "check": "examples",
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                        "output": "Running examples in ‘BIRDS-Ex.R’ failed\nThe error most likely occurred in:\n\n> base::assign(\".ptime\", proc.time(), pos = \"CheckExEnv\")\n> ### Name: listSpecies\n> ### Title: Lists all species names from the data set\n> ### Aliases: listSpecies\n> \n> ### ** Examples\n> \n> OB <- organizeBirds(bombusObsShort, sppCol = \"scientificName\", simplifySppName = TRUE)\nError: Service Unavailable (HTTP 503)\nExecution halted",
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                        "output": "Error(s) in re-building vignettes:\n  ...\n--- re-building ‘BIRDS.Rmd’ using rmarkdown\n--- finished re-building ‘BIRDS.Rmd’\n\n--- re-building ‘technical_details.Rmd’ using rmarkdown\n--- finished re-building ‘technical_details.Rmd’\n\n--- re-building ‘working_with_xts_timeseries.Rmd’ using rmarkdown\nLoading required package: zoo\n\nAttaching package: 'zoo'\n\nThe following objects are masked from 'package:base':\n\n    as.Date, as.Date.numeric\n\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded datum WGS_1984 in Proj4 definition\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  NULL source CRS comment, falling back to PROJ string\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  +init dropped in PROJ string\nWarning in wkt(obj) : CRS object has no comment\nWarning in proj4string(obj) :\n  CRS object has comment, which is lost in output\nQuitting from lines 26-43 (working_with_xts_timeseries.Rmd) \nError: processing vignette 'working_with_xts_timeseries.Rmd' failed with diagnostics:\nService Unavailable (HTTP 503)\n--- failed re-building ‘working_with_xts_timeseries.Rmd’\n\nSUMMARY: processing the following file failed:\n  ‘working_with_xts_timeseries.Rmd’\n\nError: Vignette re-building failed.\nExecution halted",
                        "check": "re-building of vignette outputs",
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                        "output": "Package suggested but not available for checking: ‘dggridR’\n\nImports includes 21 non-default packages.\nImporting from so many packages makes the package vulnerable to any of\nthem becoming unavailable.  Move as many as possible to Suggests and\nuse conditionally.",
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                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
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                            "r-devel-linux-x86_64-fedora-gcc",
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                            "r-release-macos-x86_64",
                            "r-oldrel-macos-x86_64"
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                    },
                    {
                        "version": "0.1.2",
                        "output": "Running examples in ‘BIRDS-Ex.R’ failed\nThe error most likely occurred in:\n\n> ### Name: listSpecies\n> ### Title: Lists all species names from the data set\n> ### Aliases: listSpecies\n> \n> ### ** Examples\n> \n> OB <- organizeBirds(bombusObsShort, sppCol = \"scientificName\", simplifySppName = TRUE)\nError: Service Unavailable (HTTP 503)\nExecution halted",
                        "check": "examples",
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                            "r-devel-linux-x86_64-fedora-clang"
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                    {
                        "version": "0.1.2",
                        "output": "Error(s) in re-building vignettes:\n--- re-building ‘BIRDS.Rmd’ using rmarkdown\n--- finished re-building ‘BIRDS.Rmd’\n\n--- re-building ‘technical_details.Rmd’ using rmarkdown\n--- finished re-building ‘technical_details.Rmd’\n\nsh: line 1: 3806316 Segmentation fault      (core dumped) R_LIBS=/tmp/RtmpJNaaDX/RLIBS_382e8337e78070 R_ENVIRON_USER='' R_LIBS_USER='' R_LIBS_SITE='no_such_dir' '/data/gannet/ripley/R/R-clang/bin/R' --vanilla --no-echo > '/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f073d6e39b5' 2>&1 < '/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f075951016c'\nWarning: elapsed-time limit of 30 minutes reached for sub-process\n--- re-building ‘working_with_xts_timeseries.Rmd’ using rmarkdown\nLoading required package: zoo\n\nAttaching package: 'zoo'\n\nThe following objects are masked from 'package:base':\n\n    as.Date, as.Date.numeric\n\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded datum WGS_1984 in Proj4 definition\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  NULL source CRS comment, falling back to PROJ string\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  +init dropped in PROJ string\nWarning in wkt(obj) : CRS object has no comment\nWarning in proj4string(obj) :\n  CRS object has comment, which is lost in output\n\nQuitting from lines 26-43 (working_with_xts_timeseries.Rmd) \n\n *** caught segfault ***\naddress 0x44c6, cause 'memory not mapped'\n\nTraceback:\n 1: dev.off(dv)\n 2: block_exec(params)\n 3: call_block(x)\n 4: process_group.block(group)\n 5: process_group(group)\n 6: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),     error = function(e) {        setwd(wd)        cat(res, sep = \"\\n\", file = output %n% \"\")        message(\"Quitting from lines \", paste(current_lines(i),             collapse = \"-\"), \" (\", knit_concord$get(\"infile\"),             \") \")    })\n 7: process_file(text, output)\n 8: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)\n 9: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(),     output_dir = getwd(), ...)\n10: vweave_rmarkdown(...)\n11: engine$weave(file, quiet = quiet, encoding = enc)\n12: doTryCatch(return(expr), name, parentenv, handler)\n13: tryCatchOne(expr, names, parentenv, handlers[[1L]])\n14: tryCatchList(expr, classes, parentenv, handlers)\n15: tryCatch({    engine$weave(file, quiet = quiet, encoding = enc)    setwd(startdir)    output <- find_vignette_product(name, by = \"weave\", engine = engine)    if (!have.makefile && vignette_is_tex(output)) {        texi2pdf(file = output, clean = FALSE, quiet = quiet)        output <- find_vignette_product(name, by = \"texi2pdf\",             engine = engine)    }}, error = function(e) {    OK <<- FALSE    message(gettextf(\"Error: processing vignette '%s' failed with diagnostics:\\n%s\",         file, conditionMessage(e)))})\n16: tools:::.buildOneVignette(\"working_with_xts_timeseries.Rmd\",     \"/data/gannet/ripley/R/packages/tests-clang/BIRDS.Rcheck/vign_test/BIRDS\",     TRUE, FALSE, \"working_with_xts_timeseries\", \"UTF-8\", \"/tmp/RtmpJNaaDX/working_dir/RtmpQUosnL/file398f07526f457e.rds\")\nAn irrecoverable exception occurred. R is aborting now ...\nSUMMARY: processing the following file failed:\n  ‘working_with_xts_timeseries.Rmd’\n\nError: Vignette re-building failed.\nExecution halted",
                        "check": "re-building of vignette outputs",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-clang"
                        ]
                    },
                    {
                        "version": "0.1.2",
                        "output": "Error(s) in re-building vignettes:\n--- re-building ‘BIRDS.Rmd’ using rmarkdown\nQuitting from lines 75-105 (BIRDS.Rmd) \nError: processing vignette 'BIRDS.Rmd' failed with diagnostics:\nService Unavailable (HTTP 503)\n--- failed re-building ‘BIRDS.Rmd’\n\n--- re-building ‘technical_details.Rmd’ using rmarkdown\n--- finished re-building ‘technical_details.Rmd’\n\n--- re-building ‘working_with_xts_timeseries.Rmd’ using rmarkdown\nLoading required package: zoo\n\nAttaching package: 'zoo'\n\nThe following objects are masked from 'package:base':\n\n    as.Date, as.Date.numeric\n\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs\nWarning in showSRID(uprojargs, format = \"PROJ\", multiline = \"NO\", prefer_proj = prefer_proj) :\n  Discarded datum WGS_1984 in Proj4 definition\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  NULL source CRS comment, falling back to PROJ string\nWarning in spTransform(polygon, CRSobj = CRS(\"+init=epsg:3857\")) :\n  +init dropped in PROJ string\nWarning in wkt(obj) : CRS object has no comment\nWarning in proj4string(obj) :\n  CRS object has comment, which is lost in output\n2635 observations did not overlap with the grid and will be discarded.\n0.06 % of the visits spill over neighbouring grid cells.\n--- finished re-building ‘working_with_xts_timeseries.Rmd’\n\nSUMMARY: processing the following file failed:\n  ‘BIRDS.Rmd’\n\nError: Vignette re-building failed.\nExecution halted",
                        "check": "re-building of vignette outputs",
                        "flavors": [
                            "r-devel-linux-x86_64-fedora-gcc"
                        ]
                    }
                ],
                "additional_issues": null
            }
        }
    ]
}
cchecks::cch_pkgs_search(q = "memory", one_each = TRUE, limit = 2)
$error
NULL

$count
[1] 58

$returned
[1] 2

$data
# A tibble: 2 x 5
  package date_updated      summary$any   $ok $note $warn $error $fail checks   
  <chr>   <chr>             <lgl>       <int> <int> <int>  <int> <int> <list>   
1 allan   2021-02-13T15:03TRUE            0     9     0      3     0 <df[,7]2 BIRDS   2021-02-17T15:03TRUE            3     6     1      2     0 <df[,7]# … with 1 more variable: check_details <df[,2]>

curl https://cranchecks.info/search?q=memory&one_each=true&fields=package | jq .
HTTP/2 200 
access-control-allow-methods: HEAD, GET
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 1186
date: Mon, 15 Mar 2021 13:00:50 GMT

{
    "error": null,
    "count": 58,
    "returned": 10,
    "data": [
        {
            "package": "allan",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "BIRDS",
            "date_updated": "2021-02-17T15:03:44.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "BIS",
            "date_updated": "2021-03-05T15:03:48.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "blockmodeling",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "bssm",
            "date_updated": "2021-02-23T15:03:48.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "cairoDevice",
            "date_updated": "2021-02-22T15:03:45.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "cecs",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "ChoR",
            "date_updated": "2021-03-06T15:03:46.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "clusternor",
            "date_updated": "2021-02-17T15:03:44.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        },
        {
            "package": "compboost",
            "date_updated": "2021-02-13T15:03:47.000Z",
            "summary": null,
            "checks": null,
            "check_details": null
        }
    ]
}
cchecks::cch_pkgs_search(q = "memory", one_each = TRUE, fields = "package")
$error
NULL

$count
[1] 58

$returned
[1] 30

$data
# A tibble: 30 x 5
   package       date_updated             summary checks check_details
   <chr>         <chr>                    <lgl>   <lgl>  <lgl>        
 1 allan         2021-02-13T15:03:47.000Z NA      NA     NA           
 2 BIRDS         2021-02-17T15:03:44.000Z NA      NA     NA           
 3 BIS           2021-03-05T15:03:48.000Z NA      NA     NA           
 4 blockmodeling 2021-02-13T15:03:47.000Z NA      NA     NA           
 5 bssm          2021-02-23T15:03:48.000Z NA      NA     NA           
 6 cairoDevice   2021-02-22T15:03:45.000Z NA      NA     NA           
 7 cecs          2021-02-13T15:03:47.000Z NA      NA     NA           
 8 ChoR          2021-03-06T15:03:46.000Z NA      NA     NA           
 9 clusternor    2021-02-17T15:03:44.000Z NA      NA     NA           
10 compboost     2021-02-13T15:03:47.000Z NA      NA     NA           
# … with 20 more rows

Notifications

The Notifications endpoint allow you to manage notifications sent to your email address, so you might get aware of failing CRAN checks before CRAN emails you! 💃 🔥

Notifications token

Get a token for CRAN checks notifications.

Function of the cchecks R package: cchn_register().

GET [/notifications/token]

Parameter:

email
email address

The token is sent by email, not returned via the response body or headers!

curl https://cranchecks.info/notifications/token?email=msmaellesalmon@gmail.com | jq .
HTTP/2 200 
content-type: application/json
server: Caddy
x-content-type-options: nosniff
content-length: 43
date: Sat, 16 May 2020 14:12:34 GMT

{
    "error": null,
    "data": "success, email sent"
}
# Interactively
cchecks::cchn_register(email = "jane.doe@cranchecksapidocs.com")

Notifications rules

This section is not about an endpoint, it is information useful for all notifications endpoint. 🤓

⚠️ All components of a rule (e.g., status or time) are combined with ‘AND’. That is, if status="warn" and time=3, the rule is “triggered” only if both of status="warn" and time=3 components match the cran checks data.

💡 If you want achieve ‘OR’ behavior make multiple rules.

Each rule can have 1 to 4 parameters:

status (str)
match against check status. one of: ok, note, warn, error, fail
time (int)
days in a row the match occurs. an integer. can only go 30 days back (history cleaned up after 30 days)
platforms (str/int)
platform the status occurs on, including negation (e.g., “-solaris”). options: solaris, osx, linux, windows, devel, release, patched, oldrel
regex (str)
a regex to match against the text of an error in check_details.output

Examples in words, and their equivalents as a Ruby hash

ERROR for 3 days in a row across 2 or more platforms
{'status' => 'error', 'time' => 3, 'platforms' => 2, 'regex' => nil}
ERROR for 2 days in a row on all osx platforms
{'status' => 'error', 'time' => 2, 'platforms' => "osx", 'regex' => nil}
ERROR for 2 days in a row on all release R versions
{'status' => 'error', 'time' => 2, 'platforms' => "release", 'regex' => nil}
WARN for 4 days in a row on any platform except Solaris
{'status' => 'warn', 'time' => 4, 'platforms' => "-solaris", 'regex' => nil}
WARN for 2 days in a row across 9 or more platforms
{'status' => 'warn', 'time' => 2, 'platforms' => 10, 'regex' => nil}
NOTE across all osx platforms
{'status' => 'note', 'time' => nil, 'platforms' => "osx", 'regex' => nil}
NOTE
{'status' => 'note', 'time' => nil, 'platforms' => nil, 'regex' => nil}
error details contain regex ‘install’
{'status' => nil, 'time' => nil, 'platforms' => nil, 'regex' => "install"}

Notifications create

Add new notification rules.

Functions of the cchecks R package: cchn_rule_add() and cchn_pkg_rule_add().

curl -XPOST -H "Authorization: Bearer ***" \
 --data '[{"package": "ropenaq", "regex": "install failure"}]' \
 https://cranchecks.info/notifications/rules | jq .
HTTP/2 200 
access-control-allow-methods: POST
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 131
date: Mon, 15 Mar 2021 12:59:37 GMT

{
    "error": null,
    "data": [
        {
            "id": 509,
            "already_existed": false,
            "rule": "package:ropenaq, status:, flavor:, time:, regex:install failure"
        }
    ]
}
curl -XPOST -H "Authorization: Bearer ***" \
 --data '[{"package": "ropenaq", "regex": "install failure"}]' \
 https://cranchecks.info/notifications/rules | jq .
HTTP/2 200 
access-control-allow-methods: POST
access-control-allow-origin: *
cache-control: public, must-revalidate, max-age=60
content-type: application/json; charset=utf8
server: Caddy
x-content-type-options: nosniff
content-length: 130
date: Mon, 15 Mar 2021 12:59:37 GMT

{
    "error": null,
    "data": [
        {
            "id": 509,
            "already_existed": true,
            "rule": "package:ropenaq, status:, flavor:, time:, regex:install failure"
        }
    ]
}
# From anywhere
cchecks::cchn_rule_add(
  email = "msmaellesalmon@gmail.com",
  package = "ropenaq",
  regex = "install failure",
  quiet = TRUE
  )
$error
NULL

$data
   id already_existed
1 509            TRUE
                                                             rule
1 package:ropenaq, status:, flavor:, time:, regex:install failure

# Inside the ropenaq folder
cchecks::cchn_pkg_rule_add(regex = "install failure", quiet = TRUE)
$error
NULL

$data
   id already_existed
1 509            TRUE
                                                             rule
1 package:ropenaq, status:, flavor:, time:, regex:install failure

# A second time
cchecks::cchn_pkg_rule_add(regex = "install failure", quiet = TRUE)
$error
NULL

$data
   id already_existed
1 509            TRUE
                                                             rule
1 package:ropenaq, status:, flavor:, time:, regex:install failure

Notifications list

List your notifications rules

Functions of the cchecks R package: cchn_rule_list() and cchn_pkg_rule_list().

GET [/notifications/rules]

curl https://cranchecks.info/notifications/rules -H "Authorization: Bearer ***" | jq .
HTTP/2 200 
content-type: text/html;charset=utf-8
server: Caddy
x-content-type-options: nosniff
x-frame-options: SAMEORIGIN
x-xss-protection: 1; mode=block
content-length: 143
date: Mon, 15 Mar 2021 12:59:38 GMT

{
    "error": null,
    "data": [
        {
            "id": 509,
            "package": "ropenaq",
            "rule_status": null,
            "rule_time": null,
            "rule_platforms": null,
            "rule_regex": "install failure"
        }
    ]
}
# From anywhere
cchecks::cchn_rule_list()
$error
NULL

$data
   id package rule_status rule_time rule_platforms      rule_regex
1 509 ropenaq          NA        NA             NA install failure

# Inside the ropenaq folder
cchecks::cchn_pkg_rule_list()
$error
NULL

$data
   id package rule_status rule_time rule_platforms      rule_regex
1 509 ropenaq          NA        NA             NA install failure

Notifications get

Get a notifications rule by ID

Functions of the cchecks R package: cchn_rule_get() and cchn_pkg_rule_get().

GET [/notifications/rules/{id}]

Sys.setenv("rule_id" = cchecks::cchn_rule_list()$data$id[1])
curl -H "Authorization: Bearer ***" \
 https://cranchecks.info/notifications/rules/509 | jq .
HTTP/2 200 
content-type: text/html;charset=utf-8
server: Caddy
x-content-type-options: nosniff
x-frame-options: SAMEORIGIN
x-xss-protection: 1; mode=block
content-length: 141
date: Mon, 15 Mar 2021 12:59:39 GMT

{
    "error": null,
    "data": {
        "id": 509,
        "package": "ropenaq",
        "rule_status": null,
        "rule_time": null,
        "rule_platforms": null,
        "rule_regex": "install failure"
    }
}
# From anywhere
rule_id <- cchecks::cchn_rule_list()$data$id[1]
rule_id
[1] 509

cchecks::cchn_rule_get(rule_id)
$error
NULL

$data
$data$id
[1] 509

$data$package
[1] "ropenaq"

$data$rule_status
NULL

$data$rule_time
NULL

$data$rule_platforms
NULL

$data$rule_regex
[1] "install failure"

# Inside the ropenaq folder
rule_id <- cchecks::cchn_pkg_rule_list()$data$id[1]
rule_id
[1] 509

cchecks::cchn_pkg_rule_get(rule_id)
$error
NULL

$data
$data$id
[1] 509

$data$package
[1] "ropenaq"

$data$rule_status
NULL

$data$rule_time
NULL

$data$rule_platforms
NULL

$data$rule_regex
[1] "install failure"

Notifications delete

Delete a notifications rule by ID

Functions of the cchecks R package: cchn_rule_delete() and cchn_pkg_rule_delete().

DELETE [/notifications/rules/{id}]

Sys.setenv("rule_id" = tail(cchecks::cchn_rule_list()$data, n = 1))
Error in Sys.setenv(rule_id = tail(cchecks::cchn_rule_list()$data, n = 1)): wrong length for argument
curl -XDELETE -H "Authorization: Bearer ***" \
 https://cranchecks.info/notifications/rules/509
HTTP/2 204 
access-control-allow-methods: DELETE
server: Caddy
x-content-type-options: nosniff
date: Mon, 15 Mar 2021 12:59:40 GMT

# From anywhere
rule_id <- tail(cchecks::cchn_rule_list()$data$id, n = 1)
rule_id
[1] 511

cchecks::cchn_rule_delete(rule_id)
# ok
# Inside the ropenaq folder
rule_id <- tail(cchecks::cchn_rule_list()$data$id, n = 1)
rule_id
[1] 510

cchecks::cchn_pkg_rule_delete(rule_id)
# ok