Multilevel (hierarchical) modeling: what it can and cannot do in Python

I re-read a short paper of Andrew Gelman’s yesterday about multilevel modeling, and thought “That would make a nice example for PyMC”.  The paper is “Multilevel (hierarchical) modeling: what it can and cannot do, and R code for it is on his website.
To make things even easier for a casual blogger like myself, the example [...]

MCMC in Python: PyMC for Bayesian Model Selection

(Updated 9/2/2009)
I never took a statistics class, so I only know the kind of statistics you learn on the street. But now that I’m in global health research, I’ve been doing a lot of on-the-job learning. This post is about something I’ve been reading about recently, how to decide if a simple statistical [...]

MCMC in Python: PyMC for Bayesian Probability

I’ve got an urge to write another introductory tutorial for the Python MCMC package PyMC.  This time, I say enough to the comfortable realm of Markov Chains for their own sake.  In this tutorial, I’ll test the waters of Bayesian probability.
Now, what better problem to stick my toe in than the one that inspired Reverend [...]

MCMC in Python: PyMC to sample uniformly from a convex body

This post is a little tutorial on how to use PyMC to sample points uniformly at random from a convex body.  This computational challenge says: if you have a magic box which will tell you yes/no when you ask, “Is this point (in n-dimensions) in the convex set S”, can you come up with a [...]