Re: [Pymc-user] use TkAgg?

[Christopher F. <ch...@tr...>]

On Apr 21, 2006, at 9:02 AM, Hanno Klemm wrote:
>
> I understand that the parameters to be estimated are defined via the
> sample.parameter method. There I can define a proposed distribution
> via dist='some_dist'. However, 'some_dist' needs to be zero-centered,
> if I understand the comment in the code correctly. What is the best
> way of dealing with a case where you want to have your parameters
> greater-equal than zero? Or am I missing the point completely?

Well, in theory the proposal distribution is arbitrary -- it can  
literally be any distribution over the support of the parameter. In  
practice, however, some distributions work better than others. A  
noncentral proposal distribution is fine, but it may not converge as  
efficiently as a central one. I can't think of a reason a priori that  
you would want to have a nonzero expected value, but perhaps you have  
one.

At the moment, 3 proposal distributions are built-in to PyMC: normal  
(the default), uniform, and double exponential. The double  
exponential proposal is interesting because it will occasionally  
propose extreme values, due to its long tails, which can help avoid  
metastable behaviour.

I plan on releasing, with the official 1.0 version, a more  
comprehensive user's guide that will rather explicitly lay all this out.

Regards,
Chris

--
Christopher J. Fonnesbeck

Population Ecologist, Marine Mammal Section
Fish & Wildlife Research Institute (FWC)
St. Petersburg, FL

Adjunct Assistant Professor
Warnell School of Forest Resources
University of Georgia
Athens, GA

T: 727.235.5570
E: chris at trichech.us