Package: VarSelLCM
Type: Package
Title: Variable Selection for Model-Based Clustering of Mixed-Type Data
        Set with Missing Values
Version: 2.1.1
Date: 2018-04-06
Author: Matthieu Marbac and Mohammed Sedki
Maintainer: Mohammed Sedki <mohammed.sedki@u-psud.fr>
Description: Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.
License: GPL (>= 2)
Imports: methods, Rcpp (>= 0.11.1), parallel, mgcv, ggplot2, shiny
URL: http://varsellcm.r-forge.r-project.org/
LinkingTo: Rcpp, RcppArmadillo
ByteCompile: true
LazyLoad: yes
Collate: 'CheckInputs.R' 'data.R' 'model.R' 'param.R' 'results.R'
        'ICLexact.R' 'DesignOutput.R' 'Summary.R' 'Print.R'
        'VarSelLCM.R' 'RcppExports.R' 'Plot.R' 'Imputation.R'
        'withoutmixture.R' 'VarSelShiny.R' 'ARI.R' 'VarSelConvert.R'
Packaged: 2018-04-12 08:06:36 UTC; sedki
RoxygenNote: 6.0.1
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-04-12 08:42:00 UTC
Suggests: knitr, rmarkdown, dplyr, htmltools, scales, plyr
VignetteBuilder: knitr
BuildVignettes: yes
Built: R 3.3.3; x86_64-w64-mingw32; 2018-04-22 17:05:36 UTC; windows
Archs: i386, x64
