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Activity Number: 172
Type: Topic Contributed
Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract - #308848
Title: Learning Bayesian Computation from A to Z
Author(s): Aijun Gao*+ and Fanni Natanegara and Jinghui Liu and Wei Zou
Companies: inVentiv Health Clinical and Eli Lilly and Company and inVentiv Health Clinical and inVentiv Health Clinical
Keywords: Emax model ; WinBUGS ; R ; SAS ; JAGS ; Stan

Currently multiple software and languages are available for Bayesian analyses which make the learning of Bayesian computation much easier and more practical. The software and languages include WinBUGS, R, SAS, JAGS (Just Another Gibbs Sampler) and Stan. Bayesian approach to non-linear Emax models using these tools will be discussed for some simulated data. Practical issues in Bayesian computation will also be addressed along with comparisons of the tools and interfaces between different languages.

Authors who are presenting talks have a * after their name.

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