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EnglishIn 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.
Automatic identification of seasonal transfer function models by means of iterative stepwise and genetic algorithmsIn: JOURNAL OF TIME SERIES ANALYSIS. - ISSN 0143-9782. - STAMPA. - 29(2008), pp. 37-50.
| Titolo: | Automatic identification of seasonal transfer function models by means of iterative stepwise and genetic algorithms | |
| Autore/i: | CHIOGNA M; GAETAN C; MASAROTTO G. | |
| Autore/i Unibo: | ||
| Anno: | 2008 | |
| Rivista: | ||
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1111/j.1467-9892.2007.00544.x | |
| 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. | |
| Data stato definitivo: | 2018-10-11T15:19:43Z | |
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