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Automatic identification of seasonal transfer function models by means of iterative stepwise and genetic algorithms

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Abstract. 

In this article, we introduce an automatic identification procedure for transfer function models. These models are commonplace in time-series analysis, but their identification can be complex. To tackle this problem, we propose to couple a nonlinear conditional least-squares algorithm with a genetic search over the model space. We illustrate the performances of our proposal by examples on simulated and real data.
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Keywords: Genetic algorithms; model selection; subset models

Document Type: Research Article

Affiliations: 1: Università di Padova 2: Università Ca’ Foscari – Venezia

Publication date: 2008-01-01

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