Package: LINselect 1.1.5

Benjamin Auder

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.

Authors:Yannick Baraud, Christophe Giraud, Sylvie Huet

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LINselect.pdf |LINselect.html✨
LINselect/json (API)

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4 exports 0.71 score 7 dependencies 1 dependents 1 mentions 2 scripts 282 downloads

Last updated 10 months agofrom:6d46db803b. Checks:OK: 1 NOTE: 1. Indexed: yes.

Exports:penaltysimulDatatuneLassoVARselect

Dependencies:elasticnetgtoolslarsMASSmvtnormplsrandomForest