STATS 551 - Topics in Bayesian Modeling and Computation
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Waitlist Capacity:
Advisory Prerequisites:
STATS 500 and 510 as pre- or -co-requisite.
May not be repeated for credit.
Primary Instructor:

This course provides basic concepts and modern techniques of Bayesian modeling and computation with a focus on Bayesian inference and computational algorithms based on Markov Chain Monte Carlo sampling for complex models. Additional topics may vary with the instructor, and may include de Finetti-type theorems, conjugate priors and other notions of objective prior distributions, Bayesian model selection, data analysis with hierarchical models, spatiotemporal models, dynamics models and Bayesian nonparametric models. Data analysis projects are a key component of the course.

STATS 551 - Topics in Bayesian Modeling and Computation
Schedule Listing
001 (LEC)
MW 2:30PM - 4:00PM
NOTE: Data maintained by department in Wolverine Access. If no textbooks are listed below, check with the department.

ISBN: 9780387924076
A first course in Bayesian statistical methods, Author: by Peter D. Hoff., Publisher: Springer [Online-Au 2009
ISBN: 9781439840955
Bayesian data analysis, Author: Andrew Gelman ... [et al.]., Publisher: Chapman & Hall/CRC 3rd ed. 2011
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