# Wilks¶

class Wilks(*args)

Class to evaluate the Wilks number.

Parameters: randomVector : 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 to perform in order to guarantee that the empirical quantile , noted evaluated with the maximum of the sample, noted be greater than the theoretical quantile with a probability at least :

where .

Methods

 ComputeSampleSize(quantileLevel, confidenceLevel) Evaluate the size of the sample. computeQuantileBound(quantileLevel, …[, …]) Evaluate the bound of the quantile. getClassName() Accessor to the object’s name.
__init__(*args)

Initialize self. See help(type(self)) for accurate signature.

static ComputeSampleSize(quantileLevel, confidenceLevel, marginIndex=0)

Evaluate the size of the sample.

Parameters: alpha : positive float The order of the quantile we want to evaluate. beta : positive float Confidence on the evaluation of the empirical quantile. i : int Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample) w : int the Wilks number.
computeQuantileBound(quantileLevel, confidenceLevel, marginIndex=0)

Evaluate the bound of the quantile.

Parameters: alpha : positive float The order of the quantile we want to evaluate. beta : positive float Confidence on the evaluation of the empirical quantile. i : int Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample) q : Point The estimate of the quantile upper bound for the given quantile level, at the given confidence level and using the given upper statistics.
getClassName()

Accessor to the object’s name.

Returns: class_name : str The object class name (object.__class__.__name__).