Package: STPGA
Type: Package
Title: Selection of Training Populations by Genetic Algorithm
Version: 4.0
Date: 2017-02-27
Author: Deniz Akdemir
Maintainer: Deniz Akdemir <deniz.akdemir.work@gmail.com>
Description: To be utilized to select a test data calibrated training population in high dimensional prediction problems and assumes that the explanatory variables are observed for all of the individuals. Once a "good" training set is identified, the response variable can be obtained only for this set to build a model for predicting the response in the test set. The algorithms in the package can be tweaked to solve some other subset selection problems. 
License: GPL-3
Depends: R (>= 2.10)
Suggests: R.rsp, EMMREML, quadprog, UsingR, glmnet, leaps, Matrix
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2017-03-02 01:43:36 UTC; denizakdemir
Repository: CRAN
Date/Publication: 2017-03-02 08:09:19
