Rutgers University 3 credits Statistics
Bayesian inference, manipulation of joint probability distributions, probability distributions and conditional independence concepts, Monte Carlo methods, static and dynamic methods, predictive approach to Bayesian analysis, exchangeability and the de Finetti theorem, Bayesian analysis in one-layer problems, including prior, posterior, and predictive distributions, Monte Carlo methods in advanced modeling and inference problems. Calculations are done in the Splus/R computer language and BUGS, a software package for Bayesian data analysis. Prerequisite: 16:960:593
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