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

Jean-Pierre Stockis, Joseph Tadjuidje-Kamgaing and Jürgen Franke

Statistics & Probability Letters, 2008, vol. 78, issue 6, 739-742

Abstract: 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.

Keywords: Mixture; models; Neural; networks; Identifiability (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (3)

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