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A note on the identifiability of the conditional expectation for the mixtures of neural networks

  • Stockis, Jean-Pierre
  • Tadjuidje-Kamgaing, Joseph
  • Franke, Jürgen
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    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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    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 78 (2008)
    Issue (Month): 6 (April)
    Pages: 739-742

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    Handle: RePEc:eee:stapro:v:78:y:2008:i:6:p:739-742
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    1. 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.
    2. Franke Jürgen & Diagne Mabouba, 2006. "Estimating market risk with neural networks," Statistics & Risk Modeling, De Gruyter, vol. 24(2), pages 21, December.
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