Statistics

STAT 207 Intermediate Bayesian Statistical Modeling

Hierarchical modeling, linear models (regression and analysis of variance) from the Bayesian point of view, intermediate Markov chain Monte Carlo methods, generalized linear models, multivariate models, mixture models, hidden Markov models. (Formerly AMS 207.)

Requirements

Prerequisite(s): STAT 206 or STAT 206B; enrollment is restricted to graduate students or by permission of instructor.

Credits

5

Quarter offered

Spring

Instructor

The Staff, Raquel Prado, Bruno Sanso, David Draper