pkg/DESCRIPTION

   1 Package: valse
   2 Title: Variable Selection with Mixture of Models
   3 Date: 2021-05-16
   4 Version: 0.1-0
   5 Description: Two methods are implemented to cluster data with finite mixture
   6     regression models. Those procedures deal with high-dimensional covariates and
   7     responses through a variable selection procedure based on the Lasso estimator.
   8     A low-rank constraint could be added, computed for the Lasso-Rank procedure.
   9     A collection of models is constructed, varying the level of sparsity and the
  10     number of clusters, and a model is selected using a model selection criterion
  11     (slope heuristic, BIC or AIC). Details of the procedure are provided in
  12     "Model-based clustering for high-dimensional data. Application to functional data"
  13     by Emilie Devijver (2016) <arXiv:1409.1333v2>,
  14     published in Advances in Data Analysis and Clustering.
  15 Author: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr> [aut,cre],
  16     Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
  17     Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [ctb]
  18 Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
  19 Depends:
  20     R (>= 3.5.0)
  21 Imports:
  22     MASS,
  23     parallel,
  24     cowplot,
  25     ggplot2,
  26     reshape2
  27 Suggests:
  28     capushe,
  29     roxygen2
  30 URL: https://git.auder.net/?p=valse.git
  31 License: MIT + file LICENSE
  32 RoxygenNote: 7.1.1
  33 Collate:
  34     'plot_valse.R'
  35     'main.R'
  36     'selectVariables.R'
  37     'constructionModelesLassoRank.R'
  38     'constructionModelesLassoMLE.R'
  39     'computeGridLambda.R'
  40     'initSmallEM.R'
  41     'EMGrank.R'
  42     'EMGLLF.R'
  43     'generateXY.R'
  44     'A_NAMESPACE.R'
  45     'util.R'