Local-global neural networks: a new approach for nonlinear time series modelling
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.
|Date of creation:||Oct 2003|
|Date of revision:|
|Publication status:||Published in the Journal of the American Statistical Association, v.99, n. 468, p. 1092-1107, 2004|
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