Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models
近似狄利克雷与贝塔双参数过程层级模型中的 MCMC
We present some easy-to-construct random probability measures which approximate the Dirichlet process and an extension which we will call the beta two-parameter process. The nature of these constructions makes it simple to implement Markov chain Monte Carlo algorithms for fitting nonparametric hierarchical models. For the Dirichlet process, we consider a truncation approximation as well as a weak limit approximation based on a mixture of Dirichlet processes. The same type of…