GMDHreg: Regression using GMDH Algorithms

Regression using GMDH algorithms from Prof. Alexey G. Ivakhnenko. Group Method of Data Handling (GMDH), or polynomial neural networks, is a family of inductive algorithms that performs gradually complicated polynomial models and selecting the best solution by an external criterion. In other words, inductive GMDH algorithms give possibility finding automatically interrelations in data, and selecting an optimal structure of model or network. The package includes GMDH Combinatorial, GMDH MIA (Multilayered Iterative Algorithm), GMDH GIA (Generalized Iterative Algorithm) and GMDH Combinatorial with Active Neurons. An introduction of GMDH algorithms: Farlow, S.J. (1981): "The GMDH algorithm of Ivakhnenko", The American Statistician, 35(4), pp. 210-215. <doi:10.2307/2683292> Ivakhnenko A.G. (1968): "The Group Method of Data Handling - A Rival of the Method of Stochastic Approximation", Soviet Automatic Control, 13(3), pp. 43-55.

Version: 0.2.1
Depends: R (≥ 2.15)
Imports: stats, utils
Suggests: knitr, rmarkdown
Published: 2020-08-02
Author: Manuel Villacorta Tilve
Maintainer: Manuel Villacorta Tilve <mvt.oviedo at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: GMDHreg results

Downloads:

Reference manual: GMDHreg.pdf
Vignettes: GMDHreg: an R Package for GMDH Regression
Package source: GMDHreg_0.2.1.tar.gz
Windows binaries: r-devel: GMDHreg_0.2.1.zip, r-release: GMDHreg_0.2.1.zip, r-oldrel: GMDHreg_0.2.1.zip
macOS binaries: r-release: GMDHreg_0.2.1.tgz, r-oldrel: GMDHreg_0.2.1.tgz
Old sources: GMDHreg archive

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