scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
References
loc : array-like, optional
location parameter (default=0)
scale : array-like, optional
scale parameter (default=1)
size : int or tuple of ints, optional
shape of random variates (default computed from input arguments )
moments : string, optional
composed of letters [’mvsk’] specifying which moments to compute where ‘m’
= mean, ‘v’ = variance, ‘s’ = (Fisher’s) skew and ‘k’ = (Fisher’s) kurtosis. (default=’mv’)
“The Exponential Distribution: Theory, Methods and Applications”, N. Balakrishnan, Asit P. Basu
Examples
>>> import matplotlib.pyplot as plt
>>> numargs = genexpon.numargs
>>> [ a,b,c ] = [0.9,]*numargs
>>> rv = genexpon(a,b,c)
Display frozen pdf
>>> x = np.linspace(0,np.minimum(rv.dist.b,3))
>>> h=plt.plot(x,rv.pdf(x))
Check accuracy of cdf and ppf
>>> prb = genexpon.cdf(x,a,b,c)
>>> h=plt.semilogy(np.abs(x-genexpon.ppf(prb,a,b,c))+1e-20)
Random number generation
>>> R = genexpon.rvs(a,b,c,size=100)
Generalized exponential distribution (Ryu 1993)
f(x,a,b,c) = (a+b*(1-exp(-c*x))) * exp(-a*x-b*x+b/c*(1-exp(-c*x))) for x >= 0, a,b,c > 0.
a, b, c are the first, second and third shape parameters.
508 Chapter 3. Reference