`scipy.stats._continuous_distns:jf_skew_t_gen`

source: build-install/usr/lib/python3.14/site-packages/scipy/stats/_continuous_distns.py:5736

Signature

class jf_skew_t_gen(momtype = 1, a = None, b = None, xtol = 1e-14, badvalue = None, name = None, longname = None, shapes = None, seed = None)

Members

Summary

Jones and Faddy skew-t distribution.

Extended Summary

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Notes

The probability density function for jf_skew_t is:

f (x; a, b) = C_{a, b}^{- 1} (1 + \frac{x}{( a + b + x ^{2} ) ^{1/2}})^{a + 1/2} (1 - \frac{x}{( a + b + x ^{2} ) ^{1/2}})^{b + 1/2}

for real numbers $a > 0$ and $b > 0$ , where $C_{a, b} = 2^{a + b - 1} B (a, b) (a + b)^{1/2}$ , and $B$ denotes the beta function (scipy.special.beta).

When $a < b$ , the distribution is negatively skewed, and when $a > b$ , the distribution is positively skewed. If $a = b$ , then we recover the t distribution with $2 a$ degrees of freedom.

jf_skew_t takes $a$ and $b$ as shape parameters.

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Aliases

scipy.stats._continuous_distns.jf_skew_t_gen