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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.

copied from cf-staging / r-linselect
Type Size Name Uploaded Downloads Labels
conda 392.5 kB | noarch/r-linselect-1.1.3-r43hc72bb7e_3.conda  2 years and 2 months ago 1339 main
conda 392.2 kB | noarch/r-linselect-1.1.3-r42hc72bb7e_3.conda  2 years and 2 months ago 1318 main
conda 399.3 kB | noarch/r-linselect-1.1.3-r41hc72bb7e_2.tar.bz2  2 years and 10 months ago 1787 main
conda 399.0 kB | noarch/r-linselect-1.1.3-r42hc72bb7e_2.tar.bz2  2 years and 10 months ago 1700 main
conda 398.2 kB | noarch/r-linselect-1.1.3-r40hc72bb7e_1.tar.bz2  4 years and 2 months ago 2371 main
conda 398.2 kB | noarch/r-linselect-1.1.3-r41hc72bb7e_1.tar.bz2  4 years and 2 months ago 2405 main
conda 397.3 kB | noarch/r-linselect-1.1.3-r40h6115d3f_1.tar.bz2  5 years and 3 months ago 3221 main
conda 398.2 kB | noarch/r-linselect-1.1.3-r36h6115d3f_0.tar.bz2  5 years and 7 months ago 3568 main cf202003

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