Resumen de Statistical methods for modelling neural networks

Timo Teräsvirta, Marcelo C. Medeiros

• In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on sta-tistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model selection cri-teria and tests. Mis-specification tests for evaluating an estimated neural network model are considered. Forecasting with neural network models is discussed and an application to a real time series is presented. Keywords: Model mis-specification, neural computing, nonlinear forecasting, nonlinear time series, smooth transition autoregression, sunspot series, threshold autoregression