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ESTIMATION OF THE EXPONENTIAL AUTOREGRESSIVE TIME SERIES MODEL BY USING THE GENETIC ALGORITHM

✍ Scribed by Z. Shi; H. Aoyama

Publisher: Elsevier Science
Year: 1997
Tongue: English
Weight: 229 KB
Volume: 205
Category: Article
ISSN: 0022-460X
DOI: 10.1006/jsvi.1997.1048

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✦ Synopsis

Exponential autoregression (EAR) is a kind of useful non-linear time series model that has properties similar to those of non-linear random vibrations. This model is of autoregressive form with amplitude-dependent coefficients, so parameter estimation is a non-linear optimization problem. To achieve this difficult but important task, this paper introduces a new procedure of the genetic algorithm hybridized with the least squares method to estimate the model. The simulations of both artificial time series and actual data are given to show the efficiency of the proposed approach.

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