LINselect: Selection of Linear Estimators

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.

Package details

AuthorYannick Baraud, Christophe Giraud, Sylvie Huet
MaintainerBenjamin Auder <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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LINselect documentation built on Jan. 10, 2020, 9:08 a.m.