Package: LINselect
Title: Selection of Linear Estimators
Version: 1.1.3
Date: 2020-01-07
Author: Yannick Baraud, Christophe Giraud, Sylvie Huet
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
Description: Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators,
  following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) <doi:10.1214/13-AIHP539>.
  In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso,
  elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
Imports: mvtnorm, elasticnet, MASS, randomForest, pls, gtools, stats
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: latin1
NeedsCompilation: no
Packaged: 2020-01-10 00:09:34 UTC; auder
Repository: CRAN
Date/Publication: 2020-01-10 05:30:40 UTC
Built: R 4.0.2; ; 2020-07-16 01:36:08 UTC; unix
