摘要：Factor-analytic Gaussian mixtures are often employed as a model-based approach to clustering high-dimensional data. Typically, the numbers of clusters and latent factors must be fixed in advance of model fitting. The pair which optimises some model selection criterion is then chosen. For computational reasons, having the number of factors differ across clusters is rarely considered.
关键词：model-based clustering; factor analysis; Pitman-Yor process; multiplicative gamma process; adaptive Markov chain Monte Carlo
