scipy.special.nctdtrit#

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

Inverse cumulative distribution function of the non-central t distribution.

See nctdtr for more details.

Parameters:

dfarray_like: Degrees of freedom of the distribution. Should be in range (0, inf).
ncarray_like: Noncentrality parameter.
parray_like: CDF values, in range (0, 1].
outndarray, optional: Optional output array for the function results

Returns:

tscalar or ndarray: Quantiles

See also

nctdtr: CDF of the non-central t distribution.
nctdtridf: Calculate degrees of freedom, given CDF and iCDF values.
nctdtrinc: Calculate non-centrality parameter, given CDF iCDF values.

Notes

This function calculates the quantile of the non-central t distribution using the Boost Math C++ library [1].

Note that the argument order of nctdtrit is different from that of the similar ppf method of scipy.stats.nct: t is the last parameter of nctdtrit but the first parameter of scipy.stats.nct.ppf.

References

[1]

The Boost Developers. “Boost C++ Libraries”. https://www.boost.org/.

Examples

>>> from scipy.special import nctdtr, nctdtrit

Compute the CDF for several values of t:

>>> t = [0.5, 1, 1.5]
>>> p = nctdtr(3, 1, t)
>>> p
array([0.29811049, 0.46922687, 0.6257559 ])

Compute the inverse. We recover the values of t, as expected:

>>> nctdtrit(3, 1, p)
array([0.5, 1. , 1.5])