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arXiv · 1811.08595

On an Extension of Stochastic Approximation EM Algorithm for Incomplete Data Problems

Vahid Tadayon
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Abstract

The Stochastic Approximation EM (SAEM) algorithm, a variant stochastic approximation of EM, is a versatile tool for inference in incomplete data models. In this paper, we review the fundamental EM algorithm and then focus especially on the stochastic version of EM. In order to construct the SAEM, the algorithm combines EM with a variant of stochastic approximation that uses Markov chain Monte-Carlo to deal with the missing data. The algorithm is introduced in general form and can be used to a wide range of problems.

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Vahid Tadayon. 2018-11-28. On an Extension of Stochastic Approximation EM Algorithm for Incomplete Data Problems. https://arxiv.org/abs/1811.08595

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