[Scipy-tickets] [SciPy] #1344: cdf of burr distribution is incorrect
SciPy Trac
scipy-tickets@scipy....
Tue Dec 7 16:38:27 CST 2010
#1344: cdf of burr distribution is incorrect
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Reporter: chairmanK | Owner: somebody
Type: defect | Status: new
Priority: normal | Milestone: 0.9.0
Component: scipy.stats | Version: 0.8.0
Keywords: |
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Changes (by josefpktd):
* component: Other => scipy.stats
Comment:
Why do you think it is incorrect? I don't see anything wrong.
There is no guarantee that the private methods, _cdf, _pdf handle the
bounds correctly, since they are handled by the public methods, cdf,
pdf,...
{{{
>>> from scipy import stats
>>> stats.burr.cdf(0, 0.5, 0.5)
0.0
>>> stats.burr._cdf(0, 0.5, 0.5)
Traceback (most recent call last):
File "<pyshell#41>", line 1, in <module>
stats.burr._cdf(0, 0.5, 0.5)
File "c:\josef\_progs\subversion\scipy-
trunk_after\trunk\dist\scipy-0.9.0.dev6579.win32\programs\python25\lib
\site-packages\scipy\stats\distributions.py", line 2086, in _cdf
return (1+x**(-c*1.0))**(-d**1.0)
ZeroDivisionError: 0.0 cannot be raised to a negative power
>>> stats.burr._cdf(np.array(0), 0.5, 0.5)
0.0
>>> stats.burr._cdf(np.inf, 0.5, 0.5)
1.0
>>> stats.burr._cdf(1, 0.5, 0.5)
0.70710678118654757
>>> stats.burr.veccdf(1, 0.5, 0.5)
array(0.70710678118794146)
>>> stats.burr.a
0.0
>>> stats.burr.b
1.#INF
}}}
Nevertheless, in many places, I was replacing python functions like power
with numpy functions, since they are more robust in cases like this.
--
Ticket URL: <http://projects.scipy.org/scipy/ticket/1344#comment:1>
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