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June 2000 The stochastic EM algorithm: estimation and asymptotic results
Søren Feodor Nielsen
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Bernoulli 6(3): 457-489 (June 2000).

Abstract

The EM algorithm is a much used tool for maximum likelihood estimation in missing or incomplete data problems. However, calculating the conditional expectation required in the E-step of the algorithm may be infeasible, especially when this expectation is a large sum or a high-dimensional integral. Instead the expectation can be estimated by simulation. This is the common idea in the stochastic EM algorithm and the Monte Carlo EM algorithm.

Citation

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Søren Feodor Nielsen. "The stochastic EM algorithm: estimation and asymptotic results." Bernoulli 6 (3) 457 - 489, June 2000.

Information

Published: June 2000
First available in Project Euclid: 10 April 2004

zbMATH: 0981.62022
MathSciNet: MR2001F:62016

Rights: Copyright © 2000 Bernoulli Society for Mathematical Statistics and Probability

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Vol.6 • No. 3 • June 2000
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