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Neurocomputing / EEG Neurocomputing 74, 9 (2011) 1444-1449

Asymptotic properties of mixture-of-experts models

Madalina Olteanu 1, Joseph Rynkiewicz 1

(01/04/2011)

The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for simple mixture models and mixtures of multilayer perceptrons. In this paper we first study a simple example which embodies all the difficulties arising in such models. We find that in the most general case the LRTS diverges but, with additional assumptions, the behavior of such models can be totally explicated.

1 :	Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne) (SAMM)
	Université Paris I - Panthéon-Sorbonne

Domaine

:

Mathématiques/Statistiques Statistiques/Théorie

Mots Clés : Mixture of experts – Likelihood ratio statistic test – Asymptotic statistic

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Contributeur : Joseph Rynkiewicz <>

Soumis le : Jeudi 16 Décembre 2010, 15:34:19

Dernière modification le : Mercredi 27 Juillet 2011, 11:53:58