Local-global neural networks: a new approach for nonlinear time series modelling

Mayte Suarez Farinãs, Carlos Pedreira () and Marcelo Medeiros ()

No 470, Textos para discussão from Department of Economics PUC-Rio (Brazil)

Abstract: In this paper, the Local Global Neural Networks model is proposed within the context of time series models. This formulation encompasses some already existing nonlinear models and also admits the Mixture of Experts approach. We place emphasis on the linear expert case and extensively discuss the theoretical aspects of the model: stationarity conditions, existence, consistency and asymptotic normality of the parameter estimates, and model identifiability. A model building strategy is also considered and the whole procedure is illustrated with two real time-series.

Keywords: neural networks; nonlinear models; time-series; model identifiability; parameter estimation; model building; sunspot number. (search for similar items in EconPapers)
Pages: 38 pages
Date: 2003-10
New Economics Papers: this item is included in nep-ets
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Published in the Journal of the American Statistical Association, v.99, n. 468, p. 1092-1107, 2004

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Related works:
Journal Article: Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:rio:texdis:470

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