esmtools.testing.multipletests¶
-
esmtools.testing.
multipletests
(p, alpha=0.05, method=None, **multipletests_kwargs)[source]¶ Apply statsmodels.stats.multitest.multipletests for multi-dimensional xr.objects.
Parameters: - p (xr.object) – uncorrected p-values.
- alpha (optional float) – FWER, family-wise error rate. Defaults to 0.05.
- method (str) – Method used for testing and adjustment of pvalues. Can be either the full name or initial letters. Available methods are: - bonferroni : one-step correction - sidak : one-step correction - holm-sidak : step down method using Sidak adjustments - holm : step-down method using Bonferroni adjustments - simes-hochberg : step-up method (independent) - hommel : closed method based on Simes tests (non-negative) - fdr_bh : Benjamini/Hochberg (non-negative) - fdr_by : Benjamini/Yekutieli (negative) - fdr_tsbh : two stage fdr correction (non-negative) - fdr_tsbky : two stage fdr correction (non-negative)
- **multipletests_kwargs (optional dict) – is_sorted, returnsorted see statsmodels.stats.multitest.multitest
Returns: - true for hypothesis that can be rejected for given
alpha
pvals_corrected (xr.object): p-values corrected for multiple tests
Return type: reject (xr.object)
Example
>>> from esmtools.testing import multipletests >>> reject, xpvals_corrected = multipletests(p, method='fdr_bh')