DocumentCode :
2050636
Title :
Almost sure convergence of Titterington´s recursive estimator for mixture models
Author :
Wang, Shaojun ; Zhao, Yunxin
Author_Institution :
Dept. of Comput. Sci., Waterloo Univ., Ont., Canada
fYear :
2002
fDate :
2002
Firstpage :
11
Abstract :
Titterington (see Journal of Royal Statistical Society, B, vol.46, p.257-67, 1984) proposed a recursive parameter estimation algorithm for finite mixture models. However, due to the well known problem of singularities and multiple maximum, minimum and saddle points that are possible on the likelihood surfaces, convergence analysis has seldom been made in the past years. In this paper, under mild conditions, we show the global convergence of Titterington´s recursive estimator and its MAP variant for mixture models of the full regular exponential family.
Keywords :
convergence; maximum likelihood estimation; recursive estimation; stochastic processes; MAP variant; Titterington recursive estimator; almost sure convergence; finite mixture models; full regular exponential family; global convergence; likelihood surfaces; mild conditions; recursive parameter estimation; saddle points; singularities; stochastic approximation; Bayesian methods; Computer science; Convergence; H infinity control; Maximum likelihood estimation; Parameter estimation; Recursive estimation; Stochastic processes; Taylor series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on
Print_ISBN :
0-7803-7501-7
Type :
conf
DOI :
10.1109/ISIT.2002.1023283
Filename :
1023283
Link To Document :
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