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A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
Activity Details
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| CE_15C | Mon, 8/4/2014, 8:30 AM - 5:00 PM | CC-160B | |
| Nonparametric Bayesian Data Analysis — Professional Development Continuing Education Course | |||
| ASA , Section on Bayesian Statistical Science | |||
| In this short course we will discuss the use of nonparametric Bayesian inference (BNP) for a number of common statistical inference problems, including density estimation, regression, mixed effects models, classification and clustering. In the course of this discussion we review some of the popular BNP models, including Dirichlet process (DP) models, Polya tree models, DP mixtures and dependent DP (DDP) models. We will review some of the general modeling principles, including species sampling models, stick breaking priors, product partition models for random partition and normalized random measures with indpendent increments. We will briefly discuss some of the main computational algorithms and available software. Prerequisites: working knowledge of Bayesian data anlysis (at the level of a first graduate class in Bayesian inference), and basic knowledge of Markov chain Monte Carlo posterior simulation. | |||
| Instructor(s): Peter Mueller, University of Texas at Austin, Fernando Quintana, Pontificia Universidad Católica de Chile | |||
2014 JSM Online Program Home
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