Legend: Palais des congrès de Montréal = CC, Le Westin Montréal = W, Intercontinental Montréal = I
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
|
|
Tweet | ||
| CE_08C | Sun, 8/4/2013, 8:30 AM - 5:00 PM | W-Palais | |
| Practical Bayesian Computation — Continuing Education Course | |||
| ASA , Section for Statistical Programmers and Analysts | |||
| Instructor(s): Fang Chen, SAS Institute Inc. | |||
| 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 to 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 will also 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, 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 applications areas and case studies, including multi-level hierarchical models, multivariate analysis, non-linear models, meta-analysis, and survival models. Special topics that are discussed include Monte Carlo simulation, sensitivity analysis, missing data, model assessment and selection, variable subset selection, and prediction. The examples will be done using SAS (PROC MCMC), with a strong focus on technical details. Attendees should have a background equivalent to an M.S. 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. | |||
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.