Selection Threshold Optimized Empirically via Splitting

A variable selection procedure for low to moderate size linear regressions models. This method repeatedly splits the data into two sets, one for estimation and one for validation, to obtain an empirically optimized threshold which is then used to screen for variables to include in the final model.


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install.packages("STOPES")

0.1 by Marinela Capanu, 2 years ago


Browse source code at https://github.com/cran/STOPES


Authors: Marinela Capanu , Mihai Giurcanu , Colin Begg , and Mithat Gonen


Documentation:   PDF Manual  


GPL-2 license


Imports changepoint, glmnet, MASS


See at CRAN