Package: ContaminatedMixt 1.3.8
Angelo Mazza
ContaminatedMixt: Clustering and Classification with the Contaminated Normal
Fits mixtures of multivariate contaminated normal distributions (with eigen-decomposed scale matrices) via the expectation conditional- maximization algorithm under a clustering or classification paradigm Methods are described in Antonio Punzo, Angelo Mazza, and Paul D McNicholas (2018) <doi:10.18637/jss.v085.i10>.
Authors:
ContaminatedMixt_1.3.8.tar.gz
ContaminatedMixt_1.3.8.tar.gz(r-4.5-noble)ContaminatedMixt_1.3.8.tar.gz(r-4.4-noble)
ContaminatedMixt_1.3.8.tgz(r-4.4-emscripten)ContaminatedMixt_1.3.8.tgz(r-4.3-emscripten)
ContaminatedMixt.pdf |ContaminatedMixt.html✨
ContaminatedMixt/json (API)
| # Install 'ContaminatedMixt' in R: |
| install.packages('ContaminatedMixt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- wine - Wine Data Set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:130631abc1. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 27 2024 |
| R-4.5-linux-x86_64 | OK | Nov 27 2024 |
Exports:agreeCNmixtCNmixtCVCNpredictdCNgetBestModelgetClustergetCVgetDetectiongetICgetPargetPosteriorgetSizem.steprCNwhichBestwhichBestCV
Dependencies:BHcaretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmclustmgcvmixturemnormtModelMetricsmunsellmvtnormnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppArmadilloRcppGSLrecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ContaminatedMixt - Parsimonious Mixtures of Contaminated Normal Distributions | ContaminatedMixt-package ContaminatedMixt |
| Agreement Between Partitions | agree |
| Fitting for the Parsimonious Mixtures of Contaminated Normal Distributions | CNmixt CNmixtCV |
| Cluster Prediction | CNpredict predict.ContaminatedMixt |
| Multivariate Contaminated Normal Distribution | dCN rCN |
| Extractors for 'ContaminatedMixt' Class Objects. | getBestModel getCluster getCV getDetection getIC getPar getPosterior getSize print.ContaminatedMixt summary.ContaminatedMixt whichBest whichBestCV |
| M-step of the EM algorithm for Parsimonious Normal Mixtures | m.step |
| Scatterplot Matrix for ContaminatedMixt Objects | pairs.ContaminatedMixt |
| Scatterplot for ContaminatedMixt Objects | plot.ContaminatedMixt |
| Wine Data Set | wine |