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, and GMDH MIA (Multilayered Iterative Algorithm) using PRESS (Predicted Residual Error Sum of Squares Statistic) criteria. It is calculated as the sums of squares of the prediction residuals for those observations. An introduction of GMDH algorithms: Farlow, S.J. (1981): "The GMDH algorithm of Ivakhnenko", The American Statistician, 35(4), pp. 210215. <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. 4355.
Package details 


Author  Manuel Villacorta Tilve 
Maintainer  Manuel Villacorta Tilve <[email protected]> 
License  GPL3 
Version  0.1.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.