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.

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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