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Module « scipy.special »

Fonction ncfdtri - module scipy.special

Signature de la fonction ncfdtri

def ncfdtri(*args, **kwargs) 

Description

help(scipy.special.ncfdtri)

ncfdtri(x1, x2, x3, x4, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature])

ncfdtri(dfn, dfd, nc, p, out=None)

Inverse with respect to `f` of the CDF of the non-central F distribution.

See `ncfdtr` for more details.

Parameters
----------
dfn : array_like
    Degrees of freedom of the numerator sum of squares.  Range (0, inf).
dfd : array_like
    Degrees of freedom of the denominator sum of squares.  Range (0, inf).
nc : array_like
    Noncentrality parameter.  Range [0, inf).
p : array_like
    Value of the cumulative distribution function.  Must be in the
    range [0, 1].
out : ndarray, optional
    Optional output array for the function results

Returns
-------
f : scalar or ndarray
    Quantiles, i.e., the upper limit of integration.

See Also
--------
ncfdtr : CDF of the non-central F distribution.
ncfdtridfd : Inverse of `ncfdtr` with respect to `dfd`.
ncfdtridfn : Inverse of `ncfdtr` with respect to `dfn`.
ncfdtrinc : Inverse of `ncfdtr` with 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 `ncfdtri` is different from that of the
similar ``ppf`` method of `scipy.stats.ncf`. `p` is the last parameter
of `ncfdtri` but 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])

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