Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/186687 
Year of Publication: 
2001
Series/Report no.: 
Texto para discussão No. 445
Publisher: 
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia, Rio de Janeiro
Abstract: 
In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model selection criteria and tests. Misspecification 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.
JEL: 
C22
C51
C52
C61
G12
Document Type: 
Working Paper

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