X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FDESCRIPTION;h=b620b65ea52312f23c5ae9f7691deea37d695e9b;hp=72723c0482dbf3359510525e60d2996a358cf0cc;hb=6775f5b98ffc7eae7ce9d4081b23b39ce66d3c0b;hpb=3453829ed3723a2b18ac478a6b4ef5d087a9d68d

diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION
index 72723c0..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
@@ -11,12 +11,12 @@ 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
@@ -27,7 +27,7 @@ Suggests:
     testthat
 URL: http://git.auder.net/?p=valse.git
 License: MIT + file LICENSE
-RoxygenNote: 6.0.1
+RoxygenNote: 7.0.2
 Collate:
     'plot_valse.R'
     'main.R'