Package: valse
-Title: Variable Selection With Mixture Of Models
-Date: 2020-01-11
+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
Emilie Devijver, published in Advances in Data Analysis and Clustering (2016).
Author: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr> [aut,cre],
Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
- Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [aut]
+ Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [ctb]
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
Depends:
R (>= 3.5.0)
Imports:
MASS,
- parallel
+ parallel,
+ ggplot2,
+ cowplot,
+ reshape2
Suggests:
capushe,
- methods,
- roxygen2,
- testthat
+ roxygen2
URL: http://git.auder.net/?p=valse.git
License: MIT + file LICENSE
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.0
Collate:
'plot_valse.R'
'main.R'