This is documentation for an old release of SciPy (version 0.9.0). Read this page in the documentation of the latest stable release (version 1.15.0).
An Erlang continuous random variable.
Continuous 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:
Parameters : | x : array-like
q : array-like
n : array-like
loc : array-like, optional
scale : array-like, optional
size : int or tuple of ints, optional
moments : str, optional
Alternatively, the object may be called (as a function) to fix the shape, : location, and scale parameters returning a “frozen” continuous RV object: : rv = erlang(n, loc=0, scale=1) :
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Notes
Erlang distribution (Gamma with integer shape parameter)
Examples
>>> import matplotlib.pyplot as plt
>>> numargs = erlang.numargs
>>> [ n ] = [0.9,] * numargs
>>> rv = erlang(n)
Display frozen pdf
>>> x = np.linspace(0, np.minimum(rv.dist.b, 3))
>>> h = plt.plot(x, rv.pdf(x))
Check accuracy of cdf and ppf
>>> prb = erlang.cdf(x, n)
>>> h = plt.semilogy(np.abs(x - erlang.ppf(prb, n)) + 1e-20)
Random number generation
>>> R = erlang.rvs(n, size=100)
Methods
rvs(n, loc=0, scale=1, size=1) | Random variates. |
pdf(x, n, loc=0, scale=1) | Probability density function. |
cdf(x, n, loc=0, scale=1) | Cumulative density function. |
sf(x, n, loc=0, scale=1) | Survival function (1-cdf — sometimes more accurate). |
ppf(q, n, loc=0, scale=1) | Percent point function (inverse of cdf — percentiles). |
isf(q, n, loc=0, scale=1) | Inverse survival function (inverse of sf). |
stats(n, loc=0, scale=1, moments=’mv’) | Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). |
entropy(n, loc=0, scale=1) | (Differential) entropy of the RV. |
fit(data, n, loc=0, scale=1) | Parameter estimates for generic data. |