pygsti.tools.hypothesis
Tools for general statistical hypothesis testing
Module Contents
Functions
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Calculates the standard Bonferroni correction. |
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Sidak correction. |
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Generalized Bonferroni correction. |
- pygsti.tools.hypothesis.bonferroni_correction(significance: float, numtests: int) float
Calculates the standard Bonferroni correction.
This is used for reducing the “local” significance for > 1 statistical hypothesis test to guarantee maintaining a “global” significance (i.e., a family-wise error rate) of significance.
Parameters
- significancefloat
Significance of each individual test.
- numtestsint
The number of hypothesis tests performed.
Returns
The Boferroni-corrected local significance, given by significance / numtests.
- pygsti.tools.hypothesis.sidak_correction(significance: float, numtests: int) float
Sidak correction.
Convert a significance level for an individual test repeated independently, numtest times into a significance level for the whole family of tests.
https://en.wikipedia.org/wiki/sidak_correction
Parameters
- significancefloat
Significance of each individual test.
- numtestsint
The number of hypothesis tests performed.
Returns
float
- pygsti.tools.hypothesis.generalized_bonferroni_correction(significance: float, weights: numpy.ndarray, numtests: int | None = None, nested_method: Literal['bonferroni', 'sidak'] = 'bonferroni', tol: float = 1e-10) float
Generalized Bonferroni correction.
Parameters
- significancefloat
Significance of each individual test.
- weightsarray-like
An array of non-negative floating-point weights, one per individual test, that sum to 1.0.
- numtestsint
The number of hypothesis tests performed.
- nested_method{‘bonferroni’, ‘sidak’}
Which method is used to find the significance of the composite test.
- tolfloat, optional
Tolerance when checking that the weights add to 1.0.
Returns
float