AMS 241
Theory, methods, and applications of Bayesian nonparametric modeling. Prior probability models for spaces of functions. Dirichlet processes. Pólya trees. Nonparametric mixtures. Models for regression, survival analysis, categorical data analysis, and spatial statistics. Examples drawn from social, engineering, and life sciences. (Formerly Engineering 241.) Prerequisite(s): course 207. Enrollment restricted to graduate students. A. Kottas
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