scipy.stats.erlang = <scipy.stats._continuous_distns.erlang_gen object at 0x2aba9508cf10>[source]

An Erlang continuous random variable.

As an instance of the rv_continuous class, erlang 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



The Erlang distribution is a special case of the Gamma distribution, with the shape parameter a an integer. Note that this restriction is not enforced by erlang. It will, however, generate a warning the first time a non-integer value is used for the shape parameter.

Refer to gamma for examples.


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

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