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# scipy.stats.erlang

scipy.stats.erlang = <scipy.stats._continuous_distns.erlang_gen object>

  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

  `gamma`

  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 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(order, a, loc=0, scale=1) | Non-central moment of the specified order.
  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) | Parameter estimates for generic data. See scipy.stats.rv_continuous.fit for detailed documentation of the keyword arguments.
  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(confidence, a, loc=0, scale=1) | Confidence interval with equal areas around the median.