A note on the identifiability of the conditional expectation for the mixtures of neural networks
We consider a generalized mixture of nonlinear AR models, a hidden Markov model for which the autoregressive functions are single layer feedforward neural networks. The nontrivial problem of identifiability, which is usually postulated for hidden Markov models, is addressed here.
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Volume (Year): 78 (2008)
Issue (Month): 6 (April)
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- Franke Jürgen & Diagne Mabouba, 2006. "Estimating market risk with neural networks," Statistics & Risk Modeling, De Gruyter, vol. 24(2), pages 21, December.
- Gernot Grabher & Walter W. Powell (ed.), 0. "Networks," Books, Edward Elgar, volume 0, number 2771.
- Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003.
"Local-global neural networks: a new approach for nonlinear time series modelling,"
Textos para discussão
470, Department of Economics PUC-Rio (Brazil).
- Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
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