scipy.special.betainc — SciPy v1.15.2 Manual (original) (raw)

scipy.special.betainc(a, b, x, out=None) = <ufunc 'betainc'>#

Regularized incomplete beta function.

Computes the regularized incomplete beta function, defined as [1]:

\[I_x(a, b) = \frac{\Gamma(a+b)}{\Gamma(a)\Gamma(b)} \int_0^x t^{a-1}(1-t)^{b-1}dt,\]

for \(0 \leq x \leq 1\).

This function is the cumulative distribution function for the beta distribution; its range is [0, 1].

Parameters:

a, barray_like

Positive, real-valued parameters

xarray_like

Real-valued such that \(0 \leq x \leq 1\), the upper limit of integration

outndarray, optional

Optional output array for the function values

Returns:

scalar or ndarray

Value of the regularized incomplete beta function

Notes

The term regularized in the name of this function refers to the scaling of the function by the gamma function terms shown in the formula. When not qualified as regularized, the name incomplete beta function often refers to just the integral expression, without the gamma terms. One can use the function beta fromscipy.special to get this “nonregularized” incomplete beta function by multiplying the result of betainc(a, b, x) bybeta(a, b).

This function wraps the ibeta routine from the Boost Math C++ library [2].

References

Examples

Let \(B(a, b)\) be the beta function.

import scipy.special as sc

The coefficient in terms of gamma is equal to\(1/B(a, b)\). Also, when \(x=1\)the integral is equal to \(B(a, b)\). Therefore, \(I_{x=1}(a, b) = 1\) for any \(a, b\).

sc.betainc(0.2, 3.5, 1.0) 1.0

It satisfies\(I_x(a, b) = x^a F(a, 1-b, a+1, x)/ (aB(a, b))\), where \(F\) is the hypergeometric function hyp2f1:

a, b, x = 1.4, 3.1, 0.5 x**a * sc.hyp2f1(a, 1 - b, a + 1, x)/(a * sc.beta(a, b)) 0.8148904036225295 sc.betainc(a, b, x) 0.8148904036225296

This functions satisfies the relationship\(I_x(a, b) = 1 - I_{1-x}(b, a)\):

sc.betainc(2.2, 3.1, 0.4) 0.49339638807619446 1 - sc.betainc(3.1, 2.2, 1 - 0.4) 0.49339638807619446