Abstract
In this paper we propose a generalised iterative algorithm for calculating variational Bayesian estimates for a normal mixture model and investigate its convergence properties. It is shown theoretically that the variational Bayesian estimator converges locally to the maximum likelihood estimator at the rate of $O(1/{n})$ in the large sample limit.
Citation
D. M. Titterington. Bo Wang. "Convergence properties of a general algorithm for calculating variational Bayesian estimates for a normal mixture model." Bayesian Anal. 1 (3) 625 - 650, September 2006. https://doi.org/10.1214/06-BA121
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