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Postgraduate Handbook

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Bayesian Inference and Computation - MATH5960
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Campus: Kensington Campus
 
 
Career: Postgraduate
 
 
Units of Credit: 6
 
 
EFTSL: 0.12500 (more info)
 
 
Indicative Contact Hours per Week: 2
 
 
Fee Band: 2 (more info)
 
 
Further Information: See Class Timetable
 
  

Description

After describing the fundamentals of Bayesian Inference this course will examine specification of prior distributions, links between Bayesian and frequentist inference, Bayesian model comparison and Bayesian computational methods. Markov chain Monte Carlo (MCMC) methods for computations will be described and implemented using statistical packages including WinBUGS. We will illustrate the advantages of the Bayesian approach be describing Bayesian inferential methods for a variety of models including linear models and various kinds of hierarchical structured models including mixture models.

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© The University of New South Wales (CRICOS Provider No.: 00098G), 2004-2011. The information contained in this Handbook is indicative only. While every effort is made to keep this information up-to-date, the University reserves the right to discontinue or vary arrangements, programs and courses at any time without notice and at its discretion. While the University will try to avoid or minimise any inconvenience, changes may also be made to programs, courses and staff after enrolment. The University may also set limits on the number of students in a course.