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 |

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 (arm64): GMDHreg_0.2.1.tgz, r-release (x86_64): GMDHreg_0.2.1.tgz, r-oldrel: GMDHreg_0.2.1.tgz |

Old sources: | GMDHreg archive |

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