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

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Author Info
Monica Chiogna
Carlo Gaetan
Guido Masarotto
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. Copyright 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9892.2007.00544.x
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Article provided by Blackwell Publishing in its journal Journal of Time Series Analysis.

Volume (Year): 29 (2008)
Issue (Month): 1 (01)
Pages: 37-50
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Handle: RePEc:bla:jtsera:v:29:y:2008:i:1:p:37-50

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