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

chris at fisher.forestry.uga.edu chris at fisher.forestry.uga.edu
Fri Sep 24 19:47:48 CDT 2004

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.


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