lement'``: evaluate the inverse CCDF at the
      complement of `p`
    - ``'inversion'``: solve numerically for the argument at which the
      CDF is equal to `p`

    Not all `method` options are available for all distributions.
    If the selected `method` is not available, a ``NotImplementedError``
    will be raised.

Returns
-------
out : array
    The inverse CDF evaluated at the provided argument.

See Also
--------
cdf
ilogcdf

Notes
-----
Suppose a continuous probability distribution has support :math:`[l, r]`. The
inverse CDF returns its minimum value of :math:`l` at :math:`p = 0`
and its maximum value of :math:`r` at :math:`p = 1`. Because the CDF
has range :math:`[0, 1]`, the inverse CDF is only defined on the
domain :math:`[0, 1]`; for :math:`p < 0` and :math:`p > 1`, `icdf`
returns ``nan``.

The inverse CDF is also known as the quantile function, percentile function,
and percent-point function.

References
----------
.. [1] Quantile function, *Wikipedia*,
       https://en.wikipedia.org/wiki/Quantile_function

Examples
--------
Instantiate a distribution with the desired parameters:

>>> import numpy as np
>>> from scipy import stats
>>> X = stats.Uniform(a=-0.5, b=0.5)

Evaluate the inverse CDF at the desired argument:

>>> X.icdf(0.25)
-0.25
>>> np.allclose(X.cdf(X.icdf(0.25)), 0.25)
True

This function returns NaN when the argument is outside the domain.

>>> X.icdf([-0.1, 0, 1, 1.1])
array([ nan, -0.5,  0.5,  nan])

r