%feature("docstring") OT::Wilks
"Class to evaluate the Wilks number.

Available constructor:
    Wilks(*randomVector*)

Parameters
----------
randomVector : :class:`~openturns.RandomVector` of dimension 1
    Output variable of interest.

Notes
-----
This class is a static class which enables the evaluation of the Wilks number:
the minimal sample size :math:`N_{\alpha, \beta, i}` to perform in order to
garantee that the empirical quantile :math:`\alpha`, noted
:math:`\tilde{q}_{\alpha} N_{\alpha, \beta, i}` evaluated with the
:math:`(n - i)^{th}` maximum of the sample, noted :math:`X_{n - i}` be greater
than the theoretical quantile :math:`q_{\alpha}` with a probability at least
:math:`\beta`:

.. math::

    \Pset (\tilde{q}_{\alpha} N_{\alpha, \beta, i} > q_{\alpha}) > \beta

where :math:`\tilde{q}_{\alpha} N_{\alpha, \beta, i} = X_{n-i}`."

// ---------------------------------------------------------------------

%feature("docstring") OT::Wilks::ComputeSampleSize
"Evaluate the size of the sample.

Parameters
----------
alpha : positive float :math:`< 1`
    The order of the quantile we want to evaluate.
beta : positive float :math:`< 1`
    Confidence on the evaluation of the empirical quantile.
i : int
    Rank of the maximum which will evaluate the empirical quantile. Default
    :math:`i = 0` (maximum of the sample)

Returns
-------
w : int
    the Wilks number."

// ---------------------------------------------------------------------

%feature("docstring") OT::Wilks::computeQuantileBound
"Evaluate the bound of the quantile.

Parameters
----------
alpha : positive float :math:`< 1`
    The order of the quantile we want to evaluate.
beta : positive float :math:`< 1`
    Confidence on the evaluation of the empirical quantile.
i : int
    Rank of the maximum which will evaluate the empirical quantile. Default
    :math:`i = 0` (maximum of the sample)

Returns
-------
q : :class:`~openturns.Point`
    The estimate of the quantile upper bound for the given quantile level, at
    the given confidence level and using the given upper statistics."