This Python package provides statistical post-hoc tests for pairwise multiple comparisons and outlier detection algorithms.
Features
Multiple comparisons parametric and nonparametric tests (some are ported from R’s PMCMR package):
Conover, Dunn, and Nemenyi tests for use with Kruskal-Wallis test.
Quade, van Waerden, and Durbin tests.
Conover and Nemenyi tests for use with Friedman test.
Student, Mann-Whitney, Wilcoxon, and TukeyHSD tests.
All tests are capable of p adjustments for multiple pairwise comparisons.
Plotting functionality (e.g. significance plots).
Outlier detection algorithms:
Simple test based on interquartile range (IQR).
Grubbs test.
Tietjen-Moore test.
Generalized Extreme Studentized Deviate test (ESD test).
Dependencies
Compatibility
Package is compatible with Python 2 and Python 3.
Install
You can install the package with: pip install scikit-posthocs
Example
>>> import scikit_posthocs as sp
>>> x = [[1,2,3,5,1], [12,31,54], [10,12,6,74,11]]
>>> # This will return a symmetric array of p values
>>> sp.posthoc_conover(x, p_adjust = 'holm')
array([[-1. , 0.00119517, 0.00278329],
[ 0.00119517, -1. , 0.18672227],
[ 0.00278329, 0.18672227, -1. ]])
Credits
Thorsten Pohlert, PMCMR author and maintainer
1 maintainer
Metadata
1 maintainer
Release files for scikit-posthocs 0.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scikit-posthocs-0.3.4.tar.gz | 15.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scikit_posthocs-0.3.4-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 41.9 kB
Release files / scikit-posthocs-0.3.4.tar.gz
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Release files / scikit_posthocs-0.3.4-py2.py3-none-any.whl
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| Tags | Python 2 Python 3 |
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