scipy.special.ncfdtri#
- scipy.special.ncfdtri(dfn, dfd, nc, p, out=None) = <ufunc 'ncfdtri'>#
- Inverse with respect to f of the CDF of the non-central F distribution. - See - ncfdtrfor more details.- Parameters:
- dfnarray_like
- Degrees of freedom of the numerator sum of squares. Range (0, inf). 
- dfdarray_like
- Degrees of freedom of the denominator sum of squares. Range (0, inf). 
- ncarray_like
- Noncentrality parameter. Range [0, inf). 
- parray_like
- Value of the cumulative distribution function. Must be in the range [0, 1]. 
- outndarray, optional
- Optional output array for the function results 
 
- Returns:
- fscalar or ndarray
- Quantiles, i.e., the upper limit of integration. 
 
 - See also - ncfdtr
- CDF of the non-central F distribution. 
- ncfdtridfd
- Inverse of - ncfdtrwith respect to dfd.
- ncfdtridfn
- Inverse of - ncfdtrwith respect to dfn.
- ncfdtrinc
- Inverse of - ncfdtrwith respect to nc.
- scipy.stats.ncf
- Non-central F distribution. 
 - Notes - This function calculates the Quantile of the non-central f distribution using the Boost Math C++ library [1]. - Note that argument order of - ncfdtriis different from that of the similar- ppfmethod of- scipy.stats.ncf. p is the last parameter of- ncfdtribut the first parameter of- scipy.stats.ncf.ppf.- References [1]- The Boost Developers. “Boost C++ Libraries”. https://www.boost.org/. - Examples - >>> from scipy.special import ncfdtr, ncfdtri - Compute the CDF for several values of f: - >>> f = [0.5, 1, 1.5] >>> p = ncfdtr(2, 3, 1.5, f) >>> p array([ 0.20782291, 0.36107392, 0.47345752]) - Compute the inverse. We recover the values of f, as expected: - >>> ncfdtri(2, 3, 1.5, p) array([ 0.5, 1. , 1.5])