[SciPy-dev] MCMC, Kalman Filtering, AI for SciPy?

[chris at fisher.forestry.uga.edu]

On 9/24/2004, "Robert Kern" <rkern at ucsd.edu> wrote:

>
>It would be worthwhile to go make sure the MCMC design is general enough
>to accommodate other sampling strategies (specifically, I'd like to
>implement some of the ideas of Radford M. Neal[1]). Gibbs sampling from
>models specified in a manner similar to BUGS would be cool, too.
>


The MCMC algorithm I implemented is about as general as you can get: a
random-walk metropolis-hastings sampler. It avoids the conjugacy
requirement of Gibss sampling, and allows the user to select from a
number of proposal distributions. I invite you to look at the code; it
is pretty well documented.

Chris