ÃÛÌÒ´«Ã½app

Overview

Mathematics & Statistics (Sci) : Subjective probability, Bayesian statistical inference and decision making, de Finetti’s representation. Bayesian parametric methods, optimal decisions, conjugate models, methods of prior specification and elicitation, approximation methods. Hierarchical models. Computational approaches to inference, Markov chain Monte Carlo methods, Metropolis—Hastings. Nonparametric Bayesian inference.

Terms: This course is not scheduled for the 2022-2023 academic year.

Instructors: There are no professors associated with this course for the 2022-2023 academic year.

• Prerequisite: MATH 324, MATH 357, MATH 557, or equivalent, and MATH 208 or equivalent.