add some folders; more complete package structure
[valse.git] / pkg / DESCRIPTION
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493a35bf 1Package: valse
5ce95f26 2Title: Variable Selection With Mixture Of Models
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3Date: 2016-12-01
4Version: 0.1-0
22d21a22 5Description: Two methods are implemented to cluster data with finite mixture regression models.
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6 Those procedures deal with high-dimensional covariates and responses through a variable
7 selection procedure based on the Lasso estimator. A low-rank constraint could be added,
8 computed for the Lasso-Rank procedure.
9 A collection of models is constructed, varying the level of sparsity and the number of
10 clusters, and a model is selected using a model selection criterion (slope heuristic,
11 BIC or AIC). Details of the procedure are provided in 'Model-based clustering for
12 high-dimensional data. Application to functional data' by Emilie Devijver, published in
13 Advances in Data Analysis and Clustering (2016).
ef67d338 14Author: Benjamin Auder <Benjamin.Auder@math.u-psud.fr> [aut,cre],
5ce95f26 15 Emilie Devijver <Emilie.Devijver@kuleuven.be> [aut],
ef67d338 16 Benjamin Goehry <Benjamin.Goehry@math.u-psud.fr> [aut]
ef67d338 17Maintainer: Benjamin Auder <Benjamin.Auder@math.u-psud.fr>
493a35bf 18Depends:
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19 R (>= 3.0.0)
20Imports:
e3f2fe8a 21 MASS,
22 methods
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23Suggests:
24 parallel,
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25 testhat,
26 devtools,
27 rmarkdown
493a35bf 28URL: http://git.auder.net/?p=valse.git
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29License: MIT + file LICENSE
30VignetteBuilder: knitr
f2a91208 31RoxygenNote: 5.0.1