Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators. 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.
https://anaconda.org/r_test/r-linselect/badges/version.svg
https://anaconda.org/r_test/r-linselect/badges/latest_release_date.svg
https://anaconda.org/r_test/r-linselect/badges/latest_release_relative_date.svg
https://anaconda.org/r_test/r-linselect/badges/platforms.svg
https://anaconda.org/r_test/r-linselect/badges/license.svg
https://anaconda.org/r_test/r-linselect/badges/downloads.svg