[SciPy-dev] GLMs ?
Sat Aug 15 02:32:46 CDT 2009
On Aug 15, 2009, at 3:00 AM, David Warde-Farley wrote:
> On 14-Aug-09, at 7:29 PM, email@example.com wrote:
>>> FYI, I need to fit Tweedie distributions to precipitation series. I
>>> have already coded the distributions in the scipy standard, and
>>> now I
>>> need to estimate the parameters...
>>> Thanks again
> As I understand it, the Tweedie distributions are a further
> generalization of the exponential family.
> Are you saying that your
> parametric assumption is that they are Tweedie but not any of the
> standard ones like Gaussian, Poisson, Gamma?
Yes, something intermediate between Poisson and Gamma, with a variance
proportional to the mean to a power 1<=p<=2.
>> Are you trying to estimate parameters of the distribution themselves,
>> or parameters of the distribution as function of some explanatory
>> variables? In the first case, GLM won't be of much help.
> Is it that you have samples of a (nonstandard) Tweedie random variable
> that you want to regress on explanatory variables?
> You can probably do it by gradient descent but I don't foresee it
> being pretty and probably not even convex. Either way, a GLM package
> probably won't help.
I'm not sure yet whether GLMs are the way to go to my particular
problem. I'm trying to reproduce an approach to model precipitation
patterns (keeping track of both the number and intensities of rainfall
events) described in several papers. I know that at term, I'll have to
introduce extra variables and then GLMs will be the way to go. I just
wanted to check what algorithms were already available.
Thanks a lot for your comments.
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