Statistical methods for modelling neural networks
Marcelo Medeiros () and
Timo Teräsvirta ()
No 445, Textos para discussão from Department of Economics PUC-Rio (Brazil)
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-codes: C22 C51 C52 C61 G12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp, nep-ecm, nep-ent, nep-evo and nep-net
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Published in Intelligent Systems, v.9, p. 227-235, 2001
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Persistent link: https://EconPapers.repec.org/RePEc:rio:texdis:445
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