The Stochastic EM Algorithm: Estimation and Asymptotic Results
Bernoulli2000Vol. 6(3), pp. 457–457
Citations Over TimeTop 10% of 2000 papers
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.
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