This talk will discuss methods to deal with the problem of sampling from posterior distributions in statistical models with intractable normalizing constants. In the presence of intractable normalizing constants in the likelihood function, traditional MCMC methods cannot be applied. I will review the literature on this issue and present a new general and asymptotically consistent approach to deal with it. I will illustrate the method with examples from image segmentation and social network modeling.
Joint work with Nicolas Lartillot and Christian Robert.
Technical report available at: http://www.stat.lsa.umich.edu/~yvesa/ncmcmc2.pdf