Utility Functions for 'MixtComp' Outputs

Documentation for package ‘RMixtCompUtilities’ version 4.1.4

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RMixtCompUtilities-package	RMixtCompUtilities
availableModels	Available models
completeAlgo	Add the missing element to algo parameter Add the missing element to algo parameter with default values
computeDiscrimPowerClass	Discriminative power
computeDiscrimPowerVar	Discriminative power
computeSimilarityClass	Similarity
computeSimilarityVar	Similarity
convertFunctionalToVector	Convert a mixtcomp string into a list of 2 vectors
createAlgo	Create algo object
createFunctional	Create a functional in MixtComp format
formatData	Format the data parameter required by rmc
formatModel	Format the model parameter
getBIC	Get criterion value
getCompletedData	Get the completed data from MixtComp object
getEmpiricTik	Get the tik
getICL	Get criterion value
getMixtureDensity	Get the mixture density
getModel	Names and Types Getters
getParam	Get the estimated parameter
getPartition	Get the estimated class from MixtComp object
getProportion	Get the estimated parameter
getTik	Get the tik
getType	Names and Types Getters
getVarNames	Names and Types Getters
heatmapClass	Heatmap of the similarities between classes about clustering
heatmapTikSorted	Heatmap of the tik = P(Z_i=k\|x_i)
heatmapVar	Heatmap of the similarities between variables about clustering
histMisclassif	Histogram of the misclassification probabilities
plot.MixtComp	Plot of a _MixtComp_ object
plotConvergence	Convergence of algorithm
plotDataBoxplot	Boxplot per class
plotDataCI	Mean and 95%-level confidence intervals per class
plotDiscrimClass	Barplot of the discriminative power of the classes
plotDiscrimVar	Barplot of the discriminative power of the variables
plotParamConvergence	Evolution of parameters
plotProportion	Plot the mixture's proportions
print.MixtComp	Print Values
refactorCategorical	Rename a categorical value
summary.MixtComp	MixtComp Object Summaries