Package: STPGA
Type: Package
Title: Selection of Training Populations by Genetic Algorithm
Version: 7.0.2
Date: 2026-05-28
Author: Deniz Akdemir
Maintainer: Deniz Akdemir <deniz.akdemir.work@gmail.com>
Description: Advanced genetic algorithms for optimal subset selection
        in high-dimensional prediction problems. Provides efficient
        single and multi-objective optimization for training population
        selection with comprehensive criteria including A-, D-,
        E-optimality, prediction error variance (PEV), Cook's distance
        (CD), and distance-based measures. Features multi-criteria
        convergence detection, restart mechanisms, rank-based selection
        with pressure control, adaptive mutation, diversity
        preservation, and numerically stable matrix operations.
        Includes convergence diagnostics, configurable optimization
        windows, and both modern clean interfaces with legacy
        compatibility functions.
License: GPL-3
Depends: R (>= 3.5.0), AlgDesign, scales, scatterplot3d, emoa,
        grDevices, parallel
Suggests: EMMREML, quadprog, glmnet, leaps, Matrix, testthat (>=
        3.0.0), knitr, rmarkdown, digest, progress
VignetteBuilder: knitr
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 7.3.1
Repository: https://denizakdemir.r-universe.dev
Date/Publication: 2026-05-28 08:30:43 UTC
RemoteUrl: https://github.com/denizakdemir/stpga
RemoteRef: HEAD
RemoteSha: d307a34778c6acc82f101ddc54e49288df77ac9f
Packaged: 2026-07-03 14:07:19 UTC; root