scipy tutorial - Baustatik-Info-Server

Methods
nbinom.rvs(n,pr,loc=0,size=1)
nbinom.pmf(x,n,pr,loc=0)
nbinom.cdf(x,n,pr,loc=0)
nbinom.sf(x,n,pr,loc=0)
nbinom.ppf(q,n,pr,loc=0)
nbinom.isf(q,n,pr,loc=0)
nbinom.stats(n,pr,loc=0,moments=’mv’)
nbinom.entropy(n,pr,loc=0)
Alternatively, the object may be called (as a
function) to fix
the shape and location parameters returning a
“frozen” discrete RV object:
myrv = nbinom(n,pr,loc=0)
You can construct an aribtrary discrete rv where
P{X=xk} = pk
by passing to the rv_discrete initialization method
(through the values=
keyword) a tuple of sequences (xk,pk) which
describes only those values of
X (xk) that occur with nonzero probability (pk).
geom
A geometric discrete random variable.
SciPy Reference Guide, Release 0.8.dev
•random variates
•probability mass function
•cumulative density function
•survival function (1-cdf — sometimes more accurate)
•percent point function (inverse of cdf — percentiles)
•inverse survival function (inverse of sf)
•mean(‘m’,axis=0), variance(‘v’), skew(‘s’), and/or
kurtosis(‘k’)
•entropy of the RV
•frozen RV object with the same methods but holding
the given shape and location fixed.
Discrete random variables are defined from a standard form and may require some shape parameters to complete
its specification. Any optional keyword parameters can be passed to the methods of the RV object as given
below:
Examples
>>> import matplotlib.pyplot as plt
>>> numargs = geom.numargs
>>> [ pr ] = [’Replace with resonable value’,]*numargs
3.18. Statistical functions (scipy.stats) 619