Almost sure convergence of Titterington's recursive estimator for mixture models
Titterington 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 full regular exponential family.
Year of publication: |
2006
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Authors: | Wang, Shaojun ; Zhao, Yunxin |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 76.2006, 18, p. 2001-2006
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Publisher: |
Elsevier |
Keywords: | Recursive estimation Incomplete data Mixture model Regular exponential family Almost sure convergence Stochastic approximation |
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