RMixtCompUtilities-package: RMixtCompUtilities

In RMixtCompUtilities: Utility Functions for 'MixtComp' Outputs

RMixtCompUtilities

Description

MixtComp (Mixture Composer, https://github.com/modal-inria/MixtComp) is a model-based clustering package for mixed data originating from the Modal team (Inria Lille).

It has been engineered around the idea of easy and quick integration of all new univariate models, under the conditional independence assumption. Five basic models (Gaussian, Multinomial, Poisson, Weibull, NegativeBinomial) are implemented, as well as two advanced models (Func_CS and Rank_ISR). MixtComp has the ability to natively manage missing data (completely or by interval). MixtComp is used as an R package, but its internals are coded in C++ using state of the art libraries for faster computation.

This package contains plots, getters and format functions to simplify the use of RMixtComp and RMixtCompIO packages. It is recommended to use RMixtComp (instead of RMixtCompIO) which is more user-friendly.

Details

createAlgo gives you default values for required parameters.

convertFunctionalToVector, createFunctional and refactorCategorical functions help to transform data to the required format.

Getters are available to easily access some results: getBIC, getICL, getCompletedData, getParam, getTik, getEmpiricTik, getPartition, getType, getModel, getVarNames.

You can compute discriminative powers and similarities with functions: computeDiscrimPowerClass, computeDiscrimPowerVar, computeSimilarityClass, computeSimilarityVar.

Graphics functions are plot.MixtComp, heatmapClass, heatmapTikSorted, heatmapVar, histMisclassif, plotConvergence,plotDataBoxplot, plotDataCI, plotDiscrimClass, plotDiscrimVar, plotProportion.

See Also

RMixtComp RMixtCompIO Rmixmod packages

RMixtCompUtilities documentation built on Sept. 22, 2023, 5:10 p.m.