Abstract

Bayesian statistical methods have long been computationally out of reach because the analysis often requires integration of high-dimensional functions. Recent advancements in computational tools to apply Markov Chain Monte Carlo (MCMC) methods are making Bayesian data analysis accessible for all statisticians. Two such computer tools are Win-BUGS and SASR 9.2's PROC MCMC. Bayesian methodology will be introduced through discussion of fourteen statistical examples with code and computer output to demonstrate the power of these computational tools in a wide variety of settings.

Degree

MS

College and Department

Physical and Mathematical Sciences; Statistics

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2011-07-06

Document Type

Selected Project

Handle

http://hdl.lib.byu.edu/1877/etd4563

Keywords

Bayesian data analysis, WinBUGS, PROC MCMC, statistical examples

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