*****COURSES ARE SUBJECT TO CHANGE*****
Bayesian statistical methods for inference and prediction including: estimation; model selection and prediction; exchangeability; prior, likelihood, posterior, and predictive distributions; coherence and calibration; conjugate analysis; Markov Chain Monte Carlo methods for simulation-based computation; hierarchical modeling; Bayesian model diagnostics, model selection, and sensitivity analysis. Prerequisite(s): course 203. Enrollment restricted to graduate students; undergraduates may enroll by permission of the instructor.
5 Credits
Year | Fall | Winter | Spring | Summer |
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2018-19 |
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2017-18 |
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2016-17 |
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2015-16 |
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2014-15 |
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2013-14 |
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2012-13 |
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2011-12 |
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