This is documentation for an old release of SciPy (version 0.10.0). Read this page in the documentation of the latest stable release (version 1.15.1).
An exponential power 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
b : 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 = exponpow(b, loc=0, scale=1) :
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Notes
The probability density function for exponpow is:
exponpow.pdf(x, b) = b * x**(b-1) * exp(1+x**b - exp(x**b))
for x >= 0, b > 0.
Examples
>>> from scipy.stats import exponpow
>>> numargs = exponpow.numargs
>>> [ b ] = [0.9,] * numargs
>>> rv = exponpow(b)
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 = exponpow.cdf(x, b)
>>> h = plt.semilogy(np.abs(x - exponpow.ppf(prb, b)) + 1e-20)
Random number generation
>>> R = exponpow.rvs(b, size=100)
Methods
rvs(b, loc=0, scale=1, size=1) | Random variates. |
pdf(x, b, loc=0, scale=1) | Probability density function. |
logpdf(x, b, loc=0, scale=1) | Log of the probability density function. |
cdf(x, b, loc=0, scale=1) | Cumulative density function. |
logcdf(x, b, loc=0, scale=1) | Log of the cumulative density function. |
sf(x, b, loc=0, scale=1) | Survival function (1-cdf — sometimes more accurate). |
logsf(x, b, loc=0, scale=1) | Log of the survival function. |
ppf(q, b, loc=0, scale=1) | Percent point function (inverse of cdf — percentiles). |
isf(q, b, loc=0, scale=1) | Inverse survival function (inverse of sf). |
moment(n, b, loc=0, scale=1) | Non-central moment of order n |
stats(b, loc=0, scale=1, moments=’mv’) | Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). |
entropy(b, loc=0, scale=1) | (Differential) entropy of the RV. |
fit(data, b, loc=0, scale=1) | Parameter estimates for generic data. |
expect(func, b, 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(b, loc=0, scale=1) | Median of the distribution. |
mean(b, loc=0, scale=1) | Mean of the distribution. |
var(b, loc=0, scale=1) | Variance of the distribution. |
std(b, loc=0, scale=1) | Standard deviation of the distribution. |
interval(alpha, b, loc=0, scale=1) | Endpoints of the range that contains alpha percent of the distribution |