Package: cops 1.11-4
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Thomas Rusch
cops: Cluster Optimized Proximity Scaling
Multidimensional scaling (MDS) methods that aim at pronouncing the clustered appearance of the configuration (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>). They achieve this by transforming proximities/distances with explicit power functions and penalizing the fitting criterion with a clusteredness index, the OPTICS Cordillera (Rusch, Hornik & Mair, 2018, <doi:10.1080/10618600.2017.1349664>). There are two variants: One for finding the configuration directly (COPS-C) with given explicit power transformations and implicit ratio, interval and non-metric optimal scaling transformations (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for using the augmented fitting criterion to find optimal hyperparameters for the explicit transformations (P-COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different MDS models (most of the functionality in smacofx) in the COPS framework. The package further contains a function for pattern search optimization, the ``Adaptive Luus-Jaakola Algorithm'' (Rusch, Mair & Hornik, 2021,<doi:10.1080/10618600.2020.1869027>) and a functions to calculate the phi-distances for count data or histograms.
Authors:
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cops.pdf |cops.html✨
cops/json (API)
NEWS
# Install 'cops' in R: |
install.packages('cops', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/stops
- BankingCrisesDistances - Banking Crises Distances
- matchphi - Distances of MATCH-ADTC modules
Last updated 1 months agofrom:81db9684f5. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 04 2024 |
R-4.5-win | WARNING | Sep 04 2024 |
R-4.5-linux | WARNING | Sep 04 2024 |
R-4.4-win | WARNING | Sep 04 2024 |
R-4.4-mac | WARNING | Sep 04 2024 |
R-4.3-win | WARNING | Sep 04 2024 |
R-4.3-mac | WARNING | Sep 04 2024 |
Exports:copscopsccopstressMincopStressMinljoptimpcopsphidistance
Dependencies:abindanalogueaskpassbackportsbase64encbitbit64bootbrglmbroombslibcachemcandisccarcarDatacheckmateclassclicliprclustercmaescodetoolscolorspacecommonmarkcordilleracowplotcpp11crayoncrosstalkcrscubaturecurldata.tabledbscandeldirDerivdfoptimdigestdoBydoParalleldplyre1071ellipseevaluatefansifarverfastmapfontawesomeforcatsforeachforeignFormulafsgdataGeneralizedUmatrixgenericsGenSAgeometryggplot2glmnetgluegridExtragtablegtoolshavenheplotshighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvhttrisobanditeratorsjomojquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelinproglme4lpSolvemagicmagrittrMASSMatrixMatrixModelsmemoisemgcvmicemicrobenchmarkmimeminqamitmlmodelrmunsellNlcOptimnlmenloptrnnetnnlsnpnumDerivopensslordinalpanpbkrtestpermutepillarpkgconfigplotlyplotrixpolynomprettyunitsprincurveprofileModelprogressProjectionBasedClusteringpromisesproxypsopurrrquadprogquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppProgressreadrrgenoudrglrlangrmarkdownrpartRsolnprstudioapisassscalesshapeshinyshinyjsshinythemessmacofsmacofxsourcetoolsSparseMstringistringrsubplexsurvivalsystibbletidyrtidyselecttinytextruncnormtzdbucminfutf8vctrsveganviridisviridisLitevroomweightswithrwordcloudxfunxtableyaml