JSM 2015 Preliminary Program

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Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
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Activity Details

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CE_10C Sun, 8/9/2015, 8:30 AM - 5:00 PM S-Willow A
Practical Bayesian Computation (ADDED FEE) — Professional Development Continuing Education Course
ASA , Section for Statistical Programmers and Analysts
This one-day course reviews the basic concepts of Bayesian inference and focuses on the practical use of Bayesian computational methods. The objectives are to familiarize statistical programmers and practitioners with the essentials of Bayesian computing and equip them with computational tools through a series of worked-out examples that demonstrate sound practices for a variety of statistical models and Bayesian concepts. The first part of the course will review differences between classical and Bayesian approaches to inference, fundamentals of prior distributions, and concepts in estimation. The course also will cover MCMC methods and related simulation techniques, emphasizing the interpretation of convergence diagnostics in practice. The rest of the course will take a topic-driven approach that introduces Bayesian simulation and analysis and illustrates the Bayesian treatment of a wide range of statistical models using software with code explained in detail. The course will present major application areas and case studies, including multi-level hierarchical models, multivariate analysis, nonlinear models, meta-analysis, latent variable models, and survival models. Special topics include Monte Carlo simulation, sensitivity analysis, missing data, model assessment and selection, variable subset selection, and prediction. Examples will be done using SAS (PROC MCMC), with a strong focus on technical details. Attendees should have a background equivalent to an MS in applied statistics. Previous exposure to Bayesian methods is useful, but not required. Familiarity with material at the level of this text book is appropriate: Probability and Statistics (Addison Wesley), DeGroot and Schervish.
Instructor(s): Fang Chen, SAS Institute




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