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) <10.1214>.
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.10.1214>