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Almost sure convergence of Titterington's recursive estimator for mixture models

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  • Wang, Shaojun
  • Zhao, Yunxin

Abstract

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.

Suggested Citation

  • Wang, Shaojun & Zhao, Yunxin, 2006. "Almost sure convergence of Titterington's recursive estimator for mixture models," Statistics & Probability Letters, Elsevier, vol. 76(18), pages 2001-2006, December.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:18:p:2001-2006
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    Cited by:

    1. Olivier Cappé & Eric Moulines, 2009. "On‐line expectation–maximization algorithm for latent data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 593-613, June.

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