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.

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)
80STATS Grad
MW 2:30PM - 4:00PM
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