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