scipy.special.bdtri#

scipy.special.bdtri(k, n, y, out=None) = <ufunc 'bdtri'>#

Inverse function to bdtr with respect to p.

Finds the event probability p such that the sum of the terms 0 through k of the binomial probability density is equal to the given cumulative probability y.

Parameters:
karray_like

Number of successes (float), rounded down to the nearest integer.

narray_like

Number of events (float)

yarray_like

Cumulative probability (probability of k or fewer successes in n events).

outndarray, optional

Optional output array for the function values

Returns:
pscalar or ndarray

The event probability such that bdtr(lfloor k rfloor, n, p) = y.

See also

bdtr
betaincinv

Notes

The computation is carried out using the inverse beta integral function and the relation,:

1 - p = betaincinv(n - k, k + 1, y).

Wrapper for the Cephes [1] routine bdtri.

Array API Standard Support

bdtri has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library

CPU

GPU

NumPy

✅

n/a

CuPy

n/a

✅

PyTorch

✅

⛔

JAX

⚠️ no JIT

⛔

Dask

✅

n/a

See Support for the array API standard for more information.

References

[1]

Cephes Mathematical Functions Library, http://www.netlib.org/cephes/

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