[SciPy-Dev] Subversion scipy.stats irregular problem with source code example

josef.pktd@gmai... josef.pktd@gmai...
Tue Sep 28 15:05:23 CDT 2010

On Tue, Sep 28, 2010 at 3:35 PM,  <josef.pktd@gmail.com> wrote:
> On Tue, Sep 28, 2010 at 2:10 PM, Alan G Isaac <alan.isaac@gmail.com> wrote:
>> On 9/28/2010 2:01 PM, James Phillips wrote:
>>> You might consider the rate of change might be too high
>> As long as you can provide unit tests,
>> I don't see a problem.
>> But you and Skipper shd work out the details.
> The part that fits the distributions from what I can see is LGPL
> License is GNU LGPL v3, see https://launchpad.net/twolumps
> more in a short time

James, I didn't see where in pythonequations you calculate the results
statistics, e.g. aic, in the base class?

The ranking of distributions, that I have seen are based on
kolmogorov-smirnov, chisquare-test or Anderson-Darling.
I have a test script where I use kstest for the ranking, and starting
values dependent on the support, similar to twolump (but not as

As Skipper said, the fit method works pretty well for the
distributions with open support, with bound support setting the
starting parameters based the data also works ok for many of them,
e.g. like the min in twolump.
For several of the bound support distributions an option to fix the
support, (e.g. loc) would make more sense.
(generalized extreme value and generalized pareto are supposed to have
some problems with mle for a large parameter range.)

The current scipy trunk is still "experimental", in the sense that it
doesn't work for all distributions or might raise some random
exceptions. I haven't looked much at the new fit version yet. (I'm
still experimenting in statsmodels.)

Any bugs with the current code should go into trac tickets.

What I did in my test script was to split up the distributions into
open, one-sided and bound distributions, and select starting values
depending on this. I would restrict to the subset of distributions for
which MLE works or put it inside an try except ( I think pymvpa did it
this way.)


> Josef
>> Cheers,
>> Alan Isaac
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