Title: Variable Selection With Mixture Of Models
Date: 2016-12-01
Version: 0.1-0
-Description: Two methods are implemented to cluster data with finite mixture regression models.
- Those procedures deal with high-dimensional covariates and responses through a variable
- selection procedure based on the Lasso estimator. A low-rank constraint could be added,
- computed for the Lasso-Rank procedure.
- A collection of models is constructed, varying the level of sparsity and the number of
- clusters, and a model is selected using a model selection criterion (slope heuristic,
- BIC or AIC). Details of the procedure are provided in 'Model-based clustering for
- high-dimensional data. Application to functional data' by Emilie Devijver, published in
- Advances in Data Analysis and Clustering (2016).
+Description: Two methods are implemented to cluster data with finite mixture
+ regression models. Those procedures deal with high-dimensional covariates and
+ responses through a variable selection procedure based on the Lasso estimator.
+ A low-rank constraint could be added, computed for the Lasso-Rank procedure.
+ A collection of models is constructed, varying the level of sparsity and the
+ number of clusters, and a model is selected using a model selection criterion
+ (slope heuristic, BIC or AIC). Details of the procedure are provided in 'Model-
+ based clustering for high-dimensional data. Application to functional data' by
+ Emilie Devijver, published in Advances in Data Analysis and Clustering (2016).
Author: Benjamin Auder <Benjamin.Auder@math.u-psud.fr> [aut,cre],
Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [aut]
R (>= 3.0.0)
Imports:
MASS,
- methods
+ parallel
Suggests:
- parallel,
- testhat,
- devtools,
- rmarkdown
+ capushe,
+ roxygen2,
+ testhat
URL: http://git.auder.net/?p=valse.git
License: MIT + file LICENSE
-VignetteBuilder: knitr
RoxygenNote: 5.0.1
+Collate:
+ 'plot.R'
+ 'main.R'
+ 'selectVariables.R'
+ 'constructionModelesLassoRank.R'
+ 'constructionModelesLassoMLE.R'
+ 'computeGridLambda.R'
+ 'initSmallEM.R'
+ 'EMGrank.R'
+ 'EMGLLF.R'
+ 'EMGrank_R.R'
+ 'EMGLLF_R.R'
+ 'generateXY.R'
+ 'A_NAMESPACE.R'