fun.poly

Performs polynomial to use in GMDH Combinatorial.

internal

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.

Manuel Tilve

GMDHreg

Regression using GMDH Algorithms

fun.poly function

<dl><dt>X</dt>
<dd>matrix containing independent variables in the model.</dd>
<dt>G</dt>
<dd>polynomial. Default is 2, original Ivakhnenko polynomial.
0: normal regression.
1: only interaction terms.</dd></dl>

Arguments

Performs polynomial to use in GMDH Combinatorial. — fun.poly

<dl>

<dt>X</dt>
<dd>matrix containing independent variables in the model.</dd>


<dt>G</dt>
<dd>polynomial. Default is 2, original Ivakhnenko polynomial.
0: normal regression.
1: only interaction terms.</dd>

</dl>

fun.poly: Performs polynomial to use in GMDH Combinatorial.

Description

Usage

Value

Arguments