Package: STPGA
Type: Package
Title: Selection of Training Populations by Genetic Algorithm
Version: 5.2.1
Date: 2018-11-21
Author: Deniz Akdemir
Maintainer: Deniz Akdemir <deniz.akdemir.work@gmail.com>
Description: Combining Predictive Analytics and Experimental Design to Optimize Results. 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), AlgDesign, scales, scatterplot3d, emoa, grDevices
Suggests: R.rsp, EMMREML, quadprog, UsingR, glmnet, leaps, Matrix
NeedsCompilation: no
Packaged: 2018-11-24 16:30:53 UTC; denizakdemir
Repository: CRAN
Date/Publication: 2018-11-24 17:20:06 UTC
Built: R 4.6.0; ; 2026-04-26 02:04:57 UTC; unix
