Wilks¶
-
class
Wilks
(*args)¶ Class to evaluate the Wilks number.
Refer to Estimating a quantile by Wilks’ method.
- Parameters
- randomVector
RandomVector
of dimension 1 Output variable of interest.
- randomVector
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
(self, quantileLevel, …)Evaluate the bound of the quantile.
getClassName
(self)Accessor to the object’s name.
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__init__
(self, \*args)¶ Initialize self. See help(type(self)) for accurate signature.
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static
ComputeSampleSize
(quantileLevel, confidenceLevel, marginIndex=0)¶ Evaluate the size of the sample.
- Parameters
- alphapositive float
The order of the quantile we want to evaluate.
- betapositive float
Confidence on the evaluation of the empirical quantile.
- iint
Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample)
- Returns
- wint
the Wilks number.
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computeQuantileBound
(self, quantileLevel, confidenceLevel, marginIndex=0)¶ Evaluate the bound of the quantile.
- Parameters
- alphapositive float
The order of the quantile we want to evaluate.
- betapositive float
Confidence on the evaluation of the empirical quantile.
- iint
Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample)
- Returns
- 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.
- q
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getClassName
(self)¶ Accessor to the object’s name.
- Returns
- class_namestr
The object class name (object.__class__.__name__).