`scipy.stats._continuous_distns:weibull_min_gen`

source: /scipy/stats/_continuous_distns.py :2710

Signature

   class     weibull_min_gen (    momtype    =  1   ,    a    =  None   ,    b    =  None   ,    xtol    =  1e-14   ,    badvalue    =  None   ,    name    =  None   ,    longname    =  None   ,    shapes    =  None   ,    seed    =  None     )

Members

Summary

Weibull minimum continuous random variable.

Extended Summary

The Weibull Minimum Extreme Value distribution, from extreme value theory (Fisher-Gnedenko theorem), is also often simply called the Weibull distribution. It arises as the limiting distribution of the rescaled minimum of iid random variables.

%(before_notes)s

Notes

The probability density function for weibull_min is:

f (x, c) = c x^{c - 1} exp (- x^{c})

for $x > 0$ , $c > 0$ .

weibull_min takes c as a shape parameter for $c$ . (named $k$ in Wikipedia article and $a$ in numpy.random.weibull). Special shape values are $c = 1$ and $c = 2$ where Weibull distribution reduces to the expon and rayleigh distributions respectively.

Suppose X is an exponentially distributed random variable with scale s. Then Y = X**k is weibull_min distributed with shape c = 1/k and scale s**k.

%(after_notes)s

Aliases

scipy.stats._continuous_distns.weibull_min_gen