Identification of multiregime periodic autotregressive models by genetic algorithms
Language
EN
Communication dans un congrès avec actes
This item was published in
International Conference of Time Series and Forecasting, 2018, Grenade.
English Abstract
.This paper develops a procedure for identifying multiregimePeriodic AutoRegressive (PAR) models. In each regime a possibly dif-ferent PAR model is built, for which changes can be due to the seasonalmeans, the autocorrelation ...Read more >
.This paper develops a procedure for identifying multiregimePeriodic AutoRegressive (PAR) models. In each regime a possibly dif-ferent PAR model is built, for which changes can be due to the seasonalmeans, the autocorrelation structure or the variances. Number and lo-cations of changepoints which subdivide the time span are detected bymeans of Genetic Algorithms (GAs), that optimize an identification cri-terion. The method is evaluated by means of simulation studies, and isthen employed to analyze shrimp fishery data.Read less <
English Keywords
Seasonality
Structural changes
Genetic algorithm