Package: LINselect
Encoding: UTF-8
Title: Selection of Linear Estimators
Version: 1.1.6
Date: 2025-12-09
Authors@R: c(person(given = "Yannick", family = "Baraud", role = "aut"),
  person(given = "Christophe", family = "Giraud", role = "aut"),
  person(given = "Sylvie", family = "Huet", role = "aut"),
  person(given = "Benjamin", family = "Auder", role = "cre", email = "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)
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2025-12-10 06:20:28 UTC
Packaged: 2025-12-09 16:58:53 UTC; ba
Author: Yannick Baraud [aut],
  Christophe Giraud [aut],
  Sylvie Huet [aut],
  Benjamin Auder [cre]
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
Built: R 4.6.0; ; 2026-04-25 20:03:19 UTC; unix
