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Automatic identification of seasonal transfer function models by means of iterative stepwise and genetic algorithms
Author(s) -
Chiogna Monica,
Gaetan Carlo,
Masarotto Guido
Publication year - 2008
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2007.00544.x
Subject(s) - identification (biology) , algorithm , transfer function , mathematics , series (stratigraphy) , genetic algorithm , system identification , nonlinear system , least squares function approximation , non linear least squares , function (biology) , mathematical optimization , computer science , data mining , estimation theory , statistics , paleontology , botany , physics , electrical engineering , quantum mechanics , estimator , evolutionary biology , engineering , biology , measure (data warehouse)
. 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.