[SciPy-dev] Warning about remaining issues in stats.distributions ?

josef.pktd@gmai... josef.pktd@gmai...
Mon Dec 1 10:06:48 CST 2008

There are still some known failures or methods, that don't work very
well for some distributions:

* skew. kurtosis: a few remaining incorrect results, no exact test available
* entropy: returns nan in some cases, correctness of values not tested
* fit: does not converge, or does not estimate correctly for some distributions,
       this is expected since maximum likelihood does not always work
* distributions that have problems for some range of parameters
* incorrect random number generator for one discrete distribution

Is it useful to put a warning about these issues in
stats.distributions in the release?

A friend of mine is doing value-at-risk calculations for operational
risk analysis, but I am
still reluctant to recommend scipy.stats, when it is not clear whether
the results are correct or
not, although scripting in Python would be much easier than to
struggle with some
commercial package with a GUI user interface. The problem is that in
this application they are
using many distributions automatically, and not just a few that are
well tested by frequent use.

Per Brodtkorb has an improved version of distributions.py with an
additional estimation
procedure, which we can discuss as an enhancement after 0.7 is out of
the way, if there is
an interest in this.


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