# scipy.special.chndtr#

scipy.special.chndtr(x, df, nc, out=None) = <ufunc 'chndtr'>#

Non-central chi square cumulative distribution function

The cumulative distribution function is given by:

$P(\chi^{\prime 2} \vert \nu, \lambda) =\sum_{j=0}^{\infty} e^{-\lambda /2} \frac{(\lambda /2)^j}{j!} P(\chi^{\prime 2} \vert \nu + 2j),$

where $$\nu > 0$$ is the degrees of freedom (df) and $$\lambda \geq 0$$ is the non-centrality parameter (nc).

Parameters:
xarray_like

Upper bound of the integral; must satisfy x >= 0

dfarray_like

Degrees of freedom; must satisfy df > 0

ncarray_like

Non-centrality parameter; must satisfy nc >= 0

outndarray, optional

Optional output array for the function results

Returns:
xscalar or ndarray

Value of the non-central chi square cumulative distribution function.