A simulation method based on importance sampling, Gibbs and Metropolis-Hastings techniques allows to approximate the ratio between the likelihhod function computed for two different parameter values. Thus it is possible to approximate the maximum likelihood estimator in the general framework of...

We derive from analyses of several specific latent variable models an overall review of these models, under the unifying theme of their strong connections with simulation-based methods like SEm and the Gibbs sampler. We stress that the connection goes both ways, namely that these models were...

This paper develops an extension of the Riemann sum techniques of Philippe (1997b) in the setup of MCMCC algorithms. It shows that the technique applies equally well to the output of these algorithms, with similar speeds of convergence which improve upon the regular estimator. The restriction on...