This week we will give a conceptual overview of Bayesian statistical methods as well as a walkthrough/diagnostics of a fitting a hierarchical model with JAGS.
If you'd like to follow along with the in-class walkthrough, install JAGS (http://sourceforge.net/projects/mcmc-jags/). Also have the "rjags" and "R2jags" packages installed in R.
Lecture:
coming soon
JAGS Walkthrough:
forest_cover.csv data file for JAGS demonstration
jags_example_forestcover.R R code for JAGS demonstration
example_model.pdf equations matching the model
Resources:
Getting Started with JAGS and rjags: nice introductory blog post
JAGS NEWS: blog
Bayesian Task View on CRAN: lists and describes many R packages related to Bayesian statistics
The BUGS project: Evolution, critique and future directions: useful historical perspective on the broader BUGS project
John D. Cook's blog post on "Four Reasons to Use Bayesian Statistics"
John K. Kruschke's "Open Letter extolling the benefits of the bayesian approach"