A Tutorial on Bayesian Nonparametric Models

A key problem in statistical modeling is model selection, that is, how to choose a model at an appropriate level of complexity. This problem appears in many settings, most prominently in choosing the number of clustersinmixturemodelsorthenumberoffactorsinfactoranalysis.Inthistutorial,wedescribeBayesian nonparametric methods, a class of methods that side-steps this issue by allowing the data to determine the complexity of the model. This tutorial is a high-level introduction to Bayesian nonparametric methods and contains several examples of their application.