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scikit-posthocs

version 0.3.3

Statistical post-hoc analysis and outlier detection algorithms

Download: https://pypi.python.org/pypi/scikit-posthocs
Homepage: http://github.com/maximtrp/scikit-posthocs
PyPI: http://pypi.python.org/pypi/scikit-posthocs
People: Maksim Terpilowski

Description

This Python package provides statistical post-hoc tests for pairwise multiple comparisons and outlier detection algorithms.

Features

  • Multiple comparisons post-hoc tests (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).

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, np.nan], [10,12,6,74,11]]
>>> # This will return a symmetric array of p values
>>> sp.posthoc_conover(x, p_adjust = 'holm')
array([[ 0.        ,  0.00119517,  0.00278329],
       [ 0.00119517,  0.        ,  0.18672227],
       [ 0.00278329,  0.18672227,  0.        ]])

Credits

Thorsten Pohlert, PMCMR author and maintainer

Installation

PyPI

You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikit-posthocs

Using pip

You can install scikit-posthocs for yourself from the terminal by running:

pip install --user scikit-posthocs

If you want to install it for all users on your machine, do:

pip install scikit-posthocs
On Linux, do sudo pip install scikit-posthocs.

If you don't yet have the pip tool, you can get it following these instructions.

This package was discovered in PyPI.