scipy.stats.levy_stable¶

scipy.stats.levy_stable = <scipy.stats._continuous_distns.levy_stable_gen object>[source]¶

A Levy-stable continuous random variable.

As an instance of the rv_continuous class, levy_stable object inherits from it a collection of generic methods (see below for the full list), and completes them with details specific for this particular distribution.

See also

levy, levy_l

Notes

Levy-stable distribution (only random variates available – ignore other docs)

Methods

`rvs(alpha, beta, loc=0, scale=1, size=1, random_state=None)`	Random variates.
`pdf(x, alpha, beta, loc=0, scale=1)`	Probability density function.
`logpdf(x, alpha, beta, loc=0, scale=1)`	Log of the probability density function.
`cdf(x, alpha, beta, loc=0, scale=1)`	Cumulative distribution function.
`logcdf(x, alpha, beta, loc=0, scale=1)`	Log of the cumulative distribution function.
`sf(x, alpha, beta, loc=0, scale=1)`	Survival function (also defined as `1 - cdf`, but sf is sometimes more accurate).
`logsf(x, alpha, beta, loc=0, scale=1)`	Log of the survival function.
`ppf(q, alpha, beta, loc=0, scale=1)`	Percent point function (inverse of `cdf` — percentiles).
`isf(q, alpha, beta, loc=0, scale=1)`	Inverse survival function (inverse of `sf`).
`moment(n, alpha, beta, loc=0, scale=1)`	Non-central moment of order n
`stats(alpha, beta, loc=0, scale=1, moments='mv')`	Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’).
`entropy(alpha, beta, loc=0, scale=1)`	(Differential) entropy of the RV.
`fit(data, alpha, beta, loc=0, scale=1)`	Parameter estimates for generic data.
`expect(func, args=(alpha, beta), loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds)`	Expected value of a function (of one argument) with respect to the distribution.
`median(alpha, beta, loc=0, scale=1)`	Median of the distribution.
`mean(alpha, beta, loc=0, scale=1)`	Mean of the distribution.
`var(alpha, beta, loc=0, scale=1)`	Variance of the distribution.
`std(alpha, beta, loc=0, scale=1)`	Standard deviation of the distribution.
`interval(alpha, alpha, beta, loc=0, scale=1)`	Endpoints of the range that contains alpha percent of the distribution