X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FDESCRIPTION;h=ac463663660720f58de436f9cb0d13d1edf2bff7;hp=5febdc0aa7e2742e955a1ed7aa2511e5145a377f;hb=d57c255b4a437a5e9afb4ff1b939282944c18eb5;hpb=f9143bd90ee989e7fede640b4c411374be8e2099 diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION index 5febdc0..ac46366 100644 --- a/pkg/DESCRIPTION +++ b/pkg/DESCRIPTION @@ -1,6 +1,6 @@ Package: valse -Title: Variable Selection With Mixture Of Models -Date: 2016-12-01 +Title: Variable Selection with Mixture of Models +Date: 2020-03-11 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 @@ -11,21 +11,34 @@ Description: Two methods are implemented to cluster data with finite mixture (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 [aut,cre], +Author: Benjamin Auder [aut,cre], Emilie Devijver [aut], - Benjamin Goehry [aut] -Maintainer: Benjamin Auder + Benjamin Goehry [ctb] +Maintainer: Benjamin Auder Depends: - R (>= 3.0.0) + R (>= 3.5.0) Imports: MASS, - methods -Suggests: parallel, - testhat, - devtools, - rmarkdown + ggplot2, + cowplot, + reshape2 +Suggests: + capushe, + roxygen2 URL: http://git.auder.net/?p=valse.git License: MIT + file LICENSE -VignetteBuilder: knitr -RoxygenNote: 5.0.1 +RoxygenNote: 7.0.2 +Collate: + 'plot_valse.R' + 'main.R' + 'selectVariables.R' + 'constructionModelesLassoRank.R' + 'constructionModelesLassoMLE.R' + 'computeGridLambda.R' + 'initSmallEM.R' + 'EMGrank.R' + 'EMGLLF.R' + 'generateXY.R' + 'A_NAMESPACE.R' + 'util.R'