Package: RMixtCompUtilities 4.1.6

Quentin Grimonprez

RMixtCompUtilities: Utility Functions for 'MixtComp' Outputs

Mixture Composer <https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. This package contains graphical, getter and some utility functions to facilitate the analysis of 'MixtComp' output.

Authors:Vincent Kubicki [aut], Christophe Biernacki [aut], Quentin Grimonprez [aut, cre], Matthieu Marbac-Lourdelle [aut], Étienne Goffinet [ctb], Serge Iovleff [ctb], Julien Vandaele [ctb]

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RMixtCompUtilities.pdf |RMixtCompUtilities.html
RMixtCompUtilities/json (API)
NEWS

# Install 'RMixtCompUtilities' in R:
install.packages('RMixtCompUtilities', repos = c('https://modal-inria.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/modal-inria/mixtcomp/issues

On CRAN:

clusteringcppheterogeneous-datamissing-datamixed-datamixture-modelstatistics

5.29 score 13 stars 1 packages 2 scripts 302 downloads 35 exports 70 dependencies

Last updated 6 months agofrom:096093723b. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-winNOTENov 09 2024
R-4.5-linuxNOTENov 09 2024
R-4.4-winNOTENov 09 2024
R-4.4-macNOTENov 09 2024
R-4.3-winOKNov 09 2024
R-4.3-macOKNov 09 2024

Exports:availableModelscompleteAlgocomputeDiscrimPowerClasscomputeDiscrimPowerVarcomputeSimilarityClasscomputeSimilarityVarconvertFunctionalToVectorcreateAlgocreateFunctionalformatDataformatModelgetBICgetCompletedDatagetEmpiricTikgetICLgetMixtureDensitygetModelgetParamgetPartitiongetProportiongetTikgetTypegetVarNamesheatmapClassheatmapTikSortedheatmapVarhistMisclassifplotConvergenceplotDataBoxplotplotDataCIplotDiscrimClassplotDiscrimVarplotParamConvergenceplotProportionrefactorCategorical

Dependencies:askpassbase64encbslibcachemclicolorspacecpp11crosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownsassscalesstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
RMixtCompUtilitiesRMixtCompUtilities-package
Available modelsavailableModels
Add the missing element to algo parametercompleteAlgo
Discriminative powercomputeDiscrimPowerClass computeDiscrimPowerVar
SimilaritycomputeSimilarityClass computeSimilarityVar
Convert a MixtComp functional string into a list of 2 vectorsconvertFunctionalToVector
Create algo objectcreateAlgo
Create a functional in MixtComp formatcreateFunctional
Format the data parameter required by rmcformatData
Format the model parameterformatModel
Get criterion valuegetBIC getICL
Get the completed data from MixtComp objectgetCompletedData
Get the tikgetEmpiricTik getTik
Get the mixture densitygetMixtureDensity
Get the estimated parametergetParam getProportion
Get the estimated class from MixtComp objectgetPartition
Names and Types GettersgetModel getType getVarNames
Heatmap of the similarities between classes about clusteringheatmapClass
Heatmap of the tik = P(Z_i=k|x_i)heatmapTikSorted
Heatmap of the similarities between variables about clusteringheatmapVar
Histogram of the misclassification probabilitieshistMisclassif
Plot of a _MixtComp_ objectplot.MixtComp
Convergence of algorithmplotConvergence
Boxplot per classplotDataBoxplot
Mean and 95%-level confidence intervals per classplotDataCI
Barplot of the discriminative power of the classesplotDiscrimClass
Barplot of the discriminative power of the variablesplotDiscrimVar
Evolution of parametersplotParamConvergence
Plot the mixture's proportionsplotProportion
Print Valuesprint.MixtComp
Rename a categorical valuerefactorCategorical
MixtComp Object Summariessummary.MixtComp