predict.svd

Calculates svd regression model predictions for new data.

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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

predict.svd function

<dl><dt>object</dt>
<dd>An object model from fun.svd an object class 'svd'</dd>
<dt>newdata</dt>
<dd>matrix containing dependent variable in the model, wich the predictions are calculated.</dd></dl>

Arguments

Predict svd regression — predict.svd

<dl>

<dt>object</dt>
<dd>An object model from fun.svd an object class 'svd'</dd>


<dt>newdata</dt>
<dd>matrix containing dependent variable in the model, wich the predictions are calculated.</dd>

</dl>

predict.svd: Predict svd regression

Description

Usage

Arguments