SELECTION OF ARX MODELS ESTIMATED BY THE PENALIZED WEIGHTED LEAST SQUARES METHOD | Zendy

Pan Qin | Zendy; Ryuei Nishii | Zendy

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SELECTION OF ARX MODELS ESTIMATED BY THE PENALIZED WEIGHTED LEAST SQUARES METHOD

Author(s) -

Pan Qin,

Ryuei Nishii

Publication year - 2010

Publication title -

bulletin of informatics and cybernetics

Language(s) - English

Resource type - Journals

eISSN - 2435-743X

pISSN - 0286-522X

DOI - 10.5109/25904

Subject(s) - selection (genetic algorithm) , statistics , mathematics , least squares function approximation , computer science , econometrics , artificial intelligence , estimator

We consider the selection problem of auto-regressive time-series models with eXogeneous variables (ARX) estimated by Penalized Weighted Least Squares (PWLS) method. AIC and BIC are developed based on the maximum likelihood estimation. Therefore, in this research, we evaluate GIC for the ARX models estimated by PWLS. In a numerical experiment, the model selected by GIC shows an excellent performance, especially, in a target region.

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