# scipy.special.nbdtrik#

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

Inverse of nbdtr vs k.

Returns the inverse with respect to the parameter k of y = nbdtr(k, n, p), the negative binomial cumulative distribution function.

Parameters:
yarray_like

The probability of k or fewer failures before n successes (float).

narray_like

The target number of successes (positive int).

parray_like

Probability of success in a single event (float).

outndarray, optional

Optional output array for the function results

Returns:
kscalar or ndarray

The maximum number of allowed failures such that nbdtr(k, n, p) = y.

nbdtr

Cumulative distribution function of the negative binomial.

nbdtri

Inverse with respect to p of nbdtr(k, n, p).

nbdtrin

Inverse with respect to n of nbdtr(k, n, p).

Notes

Wrapper for the CDFLIB [1] Fortran routine cdfnbn.

Formula 26.5.26 of [2],

$\sum_{j=k + 1}^\infty {{n + j - 1}\choose{j}} p^n (1 - p)^j = I_{1 - p}(k + 1, n),$

is used to reduce calculation of the cumulative distribution function to that of a regularized incomplete beta $$I$$.

Computation of k involves a search for a value that produces the desired value of y. The search relies on the monotonicity of y with k.

References

[1]

Barry Brown, James Lovato, and Kathy Russell, CDFLIB: Library of Fortran Routines for Cumulative Distribution Functions, Inverses, and Other Parameters.

[2]

Milton Abramowitz and Irene A. Stegun, eds. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. New York: Dover, 1972.