wow - thats rad. i think the answer is yes - I will take a look.


On Wed, May 14, 2014 at 5:27 PM, Jai Ram Rideout
<notifications@github.com>wrote:

> In skbio/math/stats/test.py:
>
> > @@ -118,41 +119,129 @@ def safe_sum_p_log_p(a, base=None):
> >      return np.sum(nz * logs, 0)
> >
> >
> > -def G_fit(obs, exp, williams=1):
> > -    """G test for fit between two lists of counts.
> > -
> > -    Usage: test, prob = G_fit(obs, exp, williams)
> > -
> > -    obs and exp are two lists of numbers.
> > -    williams is a boolean stating whether to do the Williams correction.
> > -
> > -    SUM(2 f(obs)ln (f(obs)/f(exp)))
> > -
> > -    See Sokal and Rohlf chapter 17.
> > +def g_stat(data):
>
> Haven't looked into this extensively, but can g_stat and/or g_fit be
> removed in favor of functionality in scipy.stats? For example, these two
> functions reference the G-test in their documentation:
>
>
> http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.stats.chi2_contingency.html#scipy-stats-chi2-contingency
>
>
> http://docs.scipy.org/doc/scipy-dev/reference/generated/scipy.stats.power_divergence.html#scipy.stats.power_divergence
>
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> .
>