X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FDESCRIPTION;h=77812ed25ed40223085631507ecc029f8411a83e;hp=3b33e257e2dff5cd51e83eb25595c4e620961156;hb=1196a43d961a95abc18d3c8e777e9a4e8233e562;hpb=ea5860f1b4fc91f06e371a0b26915198474a849d

diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION
index 3b33e25..77812ed 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
@@ -11,22 +11,24 @@ 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 <Benjamin.Auder@math.u-psud.fr> [aut,cre],
+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]
-Maintainer: Benjamin Auder <Benjamin.Auder@math.u-psud.fr>
+Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
 Depends:
-    R (>= 3.0.0)
+    R (>= 3.5.0)
 Imports:
     MASS,
-    parallel
+    parallel,
+    ggplot2,
+    cowplot,
+    reshape2
 Suggests:
     capushe,
-    roxygen2,
-    testhat
+    roxygen2
 URL: http://git.auder.net/?p=valse.git
 License: MIT + file LICENSE
-RoxygenNote: 5.0.1
+RoxygenNote: 7.0.2
 Collate:
     'plot_valse.R'
     'main.R'