scipy.stats.erlang¶
- scipy.stats.erlang = <scipy.stats._continuous_distns.erlang_gen object at 0x5849690>[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 - Notes - 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. - Methods - 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 density function. - logcdf(x, a, loc=0, scale=1) - Log of the cumulative density 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 
