[SciPy-dev] Another GSoC idea
Sat Mar 28 20:18:28 CDT 2009
On 25-Mar-09, at 5:56 PM, Robert Kern wrote:
> However, once one gets enough
> distributions to be interesting and to give assurances that one has
> covered all of the use cases in the design, the student can forgo the
> remaining distributions to work on a way to combine these distribution
> objects into probabilistic models that can be converted to efficient
> MCMC, EM, or other such numerical codes for estimation.
That is indeed a compelling idea.
In what little experimentation I've done with PyMC2, it seems to be
quite well designed and it would definitely be a mistake to ignore it
in crafting such a project, it would at the very least be a good
choice as of the downstream paths for model rendering. I can't attest
to how well it copes with being scaffolding for other inference
methods, but it would be great to have all of the MCMC infrastructure
right there to test against, for example, a variational approximation
to the posterior that you've written code for (or, in the future we
are pondering, _generated_ code for).
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