anticlust

R 패키지 메타데이터와 수집 신호를 모아 봅니다.

Packages / CRAN / anticlust

anticlust

v0.8.14
Repository CRANLicense MIT + file LICENSELifecycle activeNeeds compilation yes
Package pageReferenceSourceDOI
DOI
10.32614/CRAN.package.anticlust
Reverse imports
103

Core Signals

첫 화면에서 판단해야 할 수집 신호를 먼저 배치합니다.

1
Reverse imports
103

Supported Backends

DESCRIPTION에서 감지한 backend 관련 package입니다.

0
backend package 신호가 없습니다.

Quick Facts

기본 메타데이터를 작은 카드와 토큰으로 압축합니다.

profile
Repository
CRAN
Version
0.8.14
License
MIT + file LICENSE
Lifecycle
active
Needs compilation
yes
Reverse imports
103
Last observed
2026-06-04
CRAN
cran.r-project.org/package=anticlust

수집 소스별 패키지 정보

1개 소스
CRAN
0.8.14
2026-06-04
License
MIT + file LICENSE
Depends
R (>= 3.6.0)
Imports
Matrix, RANN (>= 2.6.0), lpSolve
Suggests
knitr, MASS, Rglpk, rmarkdown, Rsymphony, tinytest, gurobi, tableone, palmerpenguins
Needs compilation
yes
Reverse imports
103
Lifecycle
active
Last observed
2026-06-04 01:07:22

이 패키지가 의존하는 패키지

5개 표시전체 12개
PackageTypeSpec
lpSolve
CRAN · 0.8.14 · 2026-06-04
ImportslpSolve
Matrix
CRAN · 0.8.14 · 2026-06-04
ImportsMatrix
RANN
CRAN · 0.8.14 · 2026-06-04
ImportsRANN (>= 2.6.0)
gurobi
CRAN · 0.8.14 · 2026-06-04
Suggestsgurobi
knitr
CRAN · 0.8.14 · 2026-06-04
Suggestsknitr
1 / 3

이 패키지를 쓰는 패키지

2개 표시전체 2개
PackageTypeSpec
CEGO
2.4.4
CRAN · 2026-06-04
Importsanticlust
chopin
0.9.9-5
CRAN · 2026-06-04
Importsanticlust
1 / 1

Reverse dependency summary

1 types
TypePackages
Imports2

패키지 페이지

Reverse imports
4
All links
49
Repository
CRAN
Version
0.8.14
Collected
2026-05-20 21:33:35
Package page
https://cran.r-project.org/web/packages/anticlust/index.html
DOI
10.32614/CRAN.package.anticlust
Citation
https://cran.r-project.org/web/packages/anticlust/citation.html
CRAN checks
https://cran.r-project.org/web/checks/check_results_anticlust.html
Reference HTML
https://cran.r-project.org/web/packages/anticlust/refman/anticlust.html
Reference PDF
https://cran.r-project.org/web/packages/anticlust/anticlust.pdf
Source package
https://cran.r-project.org/src/contrib/anticlust_0.8.14.tar.gz
Archive
https://CRAN.R-project.org/src/contrib/Archive/anticlust
Page fields
Author
Martin Papenberg [aut, cre], Meik Michalke [ctb] (centroid based clustering algorithm), Gunnar W. Klau [ths], Juliane V. Nagel [ctb] (package logo), Martin Breuer [ctb] (Bicriterion algorithm by Brusco et al.), Marie L. Schaper [ctb] (Example data set), Max Diekhoff [ctb] (Optimal maximum dispersion algorithm), Hannah Hengelbrock [ctb] (TPSDP heuristic by Yang et al.)
BugReports
https://github.com/m-Py/anticlust/issues
CRAN Checks
anticlust results
Citation
anticlust citation info
DOI
10.32614/CRAN.package.anticlust
License
MIT + file LICENSE
Maintainer
Martin Papenberg <martin.papenberg at hhu.de>
NeedsCompilation
yes
Old Sources
anticlust archive
Package Source
anticlust_0.8.14.tar.gz
Published
2026-04-15
Reference Manual
anticlust.html , anticlust.pdf
Reverse Imports
CEGO , chopin
SystemRequirements
Rendering the vignette requires pandoc (<https://pandoc.org/>).
URL
https://github.com/m-Py/anticlust , https://m-py.github.io/anticlust/
Version
0.8.14
Vignettes
Anticlustering_in_2025 ( source , R code ) Some best practices for anticlustering ( source , R code ) Using categorical variables with anticlustering ( source , R code ) Speeding up anticlustering ( source , R code ) Using the R package anticlust for stimulus selection in experiments ( source , R code )
Windows Binaries
r-devel: anticlust_0.8.14.zip , r-release: anticlust_0.8.14.zip , r-oldrel: anticlust_0.8.14.zip
MacOS Binaries
r-release (arm64): anticlust_0.8.14.tgz , r-oldrel (arm64): anticlust_0.8.14.tgz , r-release (x86_64): anticlust_0.8.14.tgz , r-oldrel (x86_64): anticlust_0.8.14.tgz
Version
0.8.14
Published
2026-04-15
DOI
10.32614/CRAN.package.anticlust
10.32614/CRAN.package.anticlust
Author
Martin Papenberg [aut, cre], Meik Michalke [ctb] (centroid based clustering algorithm), Gunnar W. Klau [ths], Juliane V. Nagel [ctb] (package logo), Martin Breuer [ctb] (Bicriterion algorithm by Brusco et al.), Marie L. Schaper [ctb] (Example data set), Max Diekhoff [ctb] (Optimal maximum dispersion algorithm), Hannah Hengelbrock [ctb] (TPSDP heuristic by Yang et al.)
https://orcid.org/0000-0002-9900-4268
Maintainer
Martin Papenberg <martin.papenberg at hhu.de>
BugReports
https://github.com/m-Py/anticlust/issues
https://github.com/m-Py/anticlust/issues
License
MIT + file LICENSE
MITLICENSE
URL
https://github.com/m-Py/anticlust , https://m-py.github.io/anticlust/
https://github.com/m-Py/anticlusthttps://m-py.github.io/anticlust/
NeedsCompilation
yes
SystemRequirements
Rendering the vignette requires pandoc (<https://pandoc.org/>).
Citation
anticlust citation info
anticlust citation info
CRAN Checks
anticlust results
anticlust results
Reference Manual
anticlust.html , anticlust.pdf
anticlust.htmlanticlust.pdf
Vignettes
Anticlustering_in_2025 ( source , R code ) Some best practices for anticlustering ( source , R code ) Using categorical variables with anticlustering ( source , R code ) Speeding up anticlustering ( source , R code ) Using the R package anticlust for stimulus selection in experiments ( source , R code )
Anticlustering_in_2025sourceR codeSome best practices for anticlusteringsourceR codeUsing categorical variables with anticlusteringsourceR codeSpeeding up anticlusteringsourceR codeUsing the R package anticlust for stimulus selection in experimentssourceR code
Package Source
anticlust_0.8.14.tar.gz
anticlust_0.8.14.tar.gz
Windows Binaries
r-devel: anticlust_0.8.14.zip , r-release: anticlust_0.8.14.zip , r-oldrel: anticlust_0.8.14.zip
anticlust_0.8.14.zipanticlust_0.8.14.zipanticlust_0.8.14.zip
MacOS Binaries
r-release (arm64): anticlust_0.8.14.tgz , r-oldrel (arm64): anticlust_0.8.14.tgz , r-release (x86_64): anticlust_0.8.14.tgz , r-oldrel (x86_64): anticlust_0.8.14.tgz
anticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgz
Old Sources
anticlust archive
anticlust archive
Reverse Imports
CEGO , chopin
CEGOchopin
Page sections 4
Documentation
Heading
Documentation
Links
[{"label":"anticlust.html","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/refman/anticlust.html"},{"label":"anticlust.pdf","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/anticlust.pdf"},{"label":"Anticlustering_in_2025","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Anticlustering_in_2025.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Anticlustering_in_2025.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Anticlustering_in_2025.R"},{"label":"Some best practices for anticlustering","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Best_practices.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Best_practices.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Best_practices.R"},{"label":"Using categorical variables with anticlustering","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Categorical_vars.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Categorical_vars.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Categorical_vars.R"},{"label":"Speeding up anticlustering","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Speeding_up_anticlustering.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Speeding_up_anticlustering.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/Speeding_up_anticlustering.R"},{"label":"Using the R package anticlust for stimulus selection in experiments","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/stimulus-selection.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/stimulus-selection.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/anticlust/vignettes/stimulus-selection.R"}]
Text
Reference manual: anticlust.html , anticlust.pdf Vignettes: Anticlustering_in_2025 ( source , R code ) Some best practices for anticlustering ( source , R code ) Using categorical variables with anticlustering ( source , R code ) Speeding up anticlustering ( source , R code ) Using the R package anticlust for stimulus selection in experiments ( source , R code )
Downloads
Heading
Downloads
Links
[{"label":"anticlust_0.8.14.tar.gz","section":"","type":"","url":"https://cran.r-project.org/src/contrib/anticlust_0.8.14.tar.gz"},{"label":"anticlust_0.8.14.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.7/anticlust_0.8.14.zip"},{"label":"anticlust_0.8.14.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.6/anticlust_0.8.14.zip"},{"label":"anticlust_0.8.14.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.5/anticlust_0.8.14.zip"},{"label":"anticlust_0.8.14.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/sonoma-arm64/contrib/4.6/anticlust_0.8.14.tgz"},{"label":"anticlust_0.8.14.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-arm64/contrib/4.5/anticlust_0.8.14.tgz"},{"label":"anticlust_0.8.14.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.6/anticlust_0.8.14.tgz"},{"label":"anticlust_0.8.14.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.5/anticlust_0.8.14.tgz"},{"label":"anticlust archive","section":"","type":"","url":"https://CRAN.R-project.org/src/contrib/Archive/anticlust"}]
Text
Package source: anticlust_0.8.14.tar.gz Windows binaries: r-devel: anticlust_0.8.14.zip , r-release: anticlust_0.8.14.zip , r-oldrel: anticlust_0.8.14.zip macOS binaries: r-release (arm64): anticlust_0.8.14.tgz , r-oldrel (arm64): anticlust_0.8.14.tgz , r-release (x86_64): anticlust_0.8.14.tgz , r-oldrel (x86_64): anticlust_0.8.14.tgz Old sources: anticlust archive
Reverse dependencies
Heading
Reverse dependencies
Links
[{"label":"CEGO","section":"","type":"","url":"https://cran.r-project.org/web/packages/CEGO/index.html"},{"label":"chopin","section":"","type":"","url":"https://cran.r-project.org/web/packages/chopin/index.html"}]
Text
Reverse imports: CEGO , chopin
Linking
Heading
Linking
Links
[{"label":"https://CRAN.R-project.org/package=anticlust","section":"","type":"","url":"https://CRAN.R-project.org/package=anticlust"}]
Text
Please use the canonical form https://CRAN.R-project.org/package=anticlust to link to this page.
Documentation 17
anticlust.htmlanticlust.pdfAnticlustering_in_2025sourceR codeSome best practices for anticlusteringsourceR codeUsing categorical variables with anticlusteringsourceR codeSpeeding up anticlusteringsourceR codeUsing the R package anticlust for stimulus selection in experimentssourceR code
Vignettes 15
Anticlustering_in_2025sourceR codeSome best practices for anticlusteringsourceR codeUsing categorical variables with anticlusteringsourceR codeSpeeding up anticlusteringsourceR codeUsing the R package anticlust for stimulus selection in experimentssourceR code
Downloads 9
anticlust_0.8.14.tar.gzanticlust_0.8.14.zipanticlust_0.8.14.zipanticlust_0.8.14.zipanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust archive
All page links 49
MatrixRANNlpSolveknitrMASSRglpkrmarkdownRsymphonytinytesttableonepalmerpenguins10.32614/CRAN.package.anticlusthttps://orcid.org/0000-0002-9900-4268https://github.com/m-Py/anticlust/issuesMITLICENSEhttps://github.com/m-Py/anticlusthttps://m-py.github.io/anticlust/anticlust citation infoanticlust resultsanticlust.htmlanticlust.pdfAnticlustering_in_2025sourceR codeSome best practices for anticlusteringsourceR codeUsing categorical variables with anticlusteringsourceR codeSpeeding up anticlusteringsourceR codeUsing the R package anticlust for stimulus selection in experimentssourceR codeanticlust_0.8.14.tar.gzanticlust_0.8.14.zipanticlust_0.8.14.zipanticlust_0.8.14.zipanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust_0.8.14.tgzanticlust archiveCEGOchopinhttps://CRAN.R-project.org/package=anticlust

버전 이력

RepositoryVersionPublishedFirst seenLast seenDocs
CRAN0.8.132025-11-292026-05-312026-05-31
CRAN0.8.122025-10-312026-05-312026-05-31
CRAN0.8.10-12025-03-262026-05-312026-05-31
CRAN0.8.102025-03-142026-05-312026-05-31
CRAN0.8.9-12025-01-202026-05-312026-05-31
CRAN0.8.92025-01-172026-05-312026-05-31
CRAN0.8.72024-10-012026-05-312026-05-31
CRAN0.8.52024-05-052026-05-312026-05-31
CRAN0.8.32024-04-242026-05-312026-05-31
CRAN0.8.12023-10-262026-05-312026-05-31
CRAN0.8.0-12023-10-252026-05-312026-05-31
CRAN0.8.02023-09-142026-05-312026-05-31
CRAN0.7.02023-07-152026-05-312026-05-31
CRAN0.6.42023-05-022026-05-312026-05-31
CRAN0.6.32023-01-302026-05-312026-05-31
CRAN0.6.12021-12-072026-05-312026-05-31
CRAN0.6.02021-12-012026-05-312026-05-31
CRAN0.5.62020-11-242026-05-312026-05-31
CRAN0.5.32020-09-252026-05-312026-05-31
CRAN0.5.02020-06-292026-05-312026-05-31
CRAN0.8.142026-06-012026-06-04

보안

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