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Paper No. 07-24

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O Papaspiliopoulos and G Sermaidis

Monotonicity Properties of the Monte Carlo EM Algorithm and Connections with Simulated Likelihood

Abstract: In this note we show that the Monte Carlo EM algorithm, appropriately constructed with importance re-weighting, monotonically increases a corresponding simulated likelihood. This is result is formally proved but also intuitively explained by a formulation of the problem using auxiliary variables.

Keywords: Importance sampling, fixed random seeds, incomplete data, latent stochastic processes.