pkg/DESCRIPTION

   1 Package: valse
   2 Title: Variable Selection With Mixture Of Models
   3 Date: 2016-12-01
   4 Version: 0.1-0
   5 Description: Two methods are implemented to cluster data with finite mixture regression models.
   6     Those procedures deal with high-dimensional covariates and responses through a variable
   7     selection procedure based on the Lasso estimator. A low-rank constraint could be added,
   8     computed for the Lasso-Rank procedure.
   9     A collection of models is constructed, varying the level of sparsity and the number of
  10     clusters, and a model is selected using a model selection criterion (slope heuristic,
  11     BIC or AIC). Details of the procedure are provided in 'Model-based clustering for
  12     high-dimensional data. Application to functional data' by Emilie Devijver, published in
  13     Advances in Data Analysis and Clustering (2016).
  14 Author: Benjamin Auder <Benjamin.Auder@math.u-psud.fr> [aut,cre],
  15     Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
  16     Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [aut]
  17 Maintainer: Benjamin Auder <Benjamin.Auder@math.u-psud.fr>
  18 Depends:
  19     R (>= 3.0.0)
  20 Imports:
  21     MASS,
  22     methods
  23 Suggests:
  24     parallel,
  25     testhat,
  26     devtools,
  27     rmarkdown
  28 URL: http://git.auder.net/?p=valse.git
  29 License: MIT + file LICENSE
  30 VignetteBuilder: knitr
  31 RoxygenNote: 6.0.1