Winter 2018

Instructor

Michele Guindani
Associate Professor
Department of Statistics
Email: michele.guindani@uci.edu
Website: http://www.micheleguindani.info
Phone: (949) 824-5968
Office Hours: W 1pm-2:30pm @ Bren Hall 2241

Time and Days

Lecture:
TuTh 2:00- 3:20p DBH 1423

Discussion:
F 9:00- 9:50 DBH 1423 (according to schedule)

COURSE DESCRIPTION:

The course will discuss the foundations of the Bayesian approach to statisticla inference. Topics include a probabilistic foundation of the prior-to-posterior update via the Bayes theorem, and a discussion of posterior consistency, prior elicitation, Bayesian point-estimation, testing and credible regions, Markov Chain Monte Carlo calculation, Model choice, hierarchical and empirical Bayes estimation.

OBJECTIVES:

Learn foundation of Bayesian analysis, including how to conduct posterior and predictive inference; posterior consistency of Bayesian estimates; foundations of Bayesian estimation and testing; Bayesian calculation; hierarchical models.

REQUIREMENTS:

Prerequisite: STATS 205 and STATS 230.

TEXTBOOK:

Instructor Notes

Robert C.P. (2007) The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation, Springer

Ghosh J.K., Delampady M., Tapas, S. (2006) An Introduction to Bayesian Analysis: Theory and Methods, Springer

Hoff P.D. (2009) A First Course in Bayesian Statistical Methods, Springer