- Volume 6, Number 3 (2000), 457-489.
The stochastic EM algorithm: estimation and asymptotic results
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.
Bernoulli, Volume 6, Number 3 (2000), 457-489.
First available in Project Euclid: 10 April 2004
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Feodor Nielsen, Søren. The stochastic EM algorithm: estimation and asymptotic results. Bernoulli 6 (2000), no. 3, 457--489. https://projecteuclid.org/euclid.bj/1081616701