Improving convergence of Data Augmentation [published]

Our paper with Jim Hobert and Vivek Roy, Improving the Convergence Properties of the Data Augmentation Algorithm with an Application to Bayesian Mixture Modeling, has now appeared in Statistical Science and is available on Project Euclid. (For IMS members, at least.) Personally, this is an important paper, not only for providing an exact convergence evaluation for mixtures,  not only for sharing exciting research days with my friends Jim and Vivek, but also for finalising a line of research somehow started in 1993 when Richard Tweedie visited me in Paris and when I visited him in Fort Collins… Coincidentally, my discussion of Don Fraser’s provocative Is Bayes Posterior just Quick and Dirty Confidence? also appeared in this issue of Statistical Science.

One Response to “Improving convergence of Data Augmentation [published]”

  1. […] ago (!), has now appeared in arXiv, Statistical Science and project Euclid. I already mentioned in a previous post why this is an important paper for me. (There is nothing new  here, compared with this earlier […]

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