X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FDESCRIPTION;h=b620b65ea52312f23c5ae9f7691deea37d695e9b;hb=04845e3300b5450629bf1a2c3344d2f9419e91a6;hp=5febdc0aa7e2742e955a1ed7aa2511e5145a377f;hpb=f9143bd90ee989e7fede640b4c411374be8e2099;p=valse.git diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION index 5febdc0..b620b65 100644 --- a/pkg/DESCRIPTION +++ b/pkg/DESCRIPTION @@ -1,6 +1,6 @@ Package: valse Title: Variable Selection With Mixture Of Models -Date: 2016-12-01 +Date: 2020-01-11 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 +11,33 @@ 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 +Maintainer: Benjamin Auder Depends: - R (>= 3.0.0) + R (>= 3.5.0) Imports: MASS, - methods + parallel Suggests: - parallel, - testhat, - devtools, - rmarkdown + capushe, + methods, + roxygen2, + testthat 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'