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Exact inference via mosaic permutations

Project description

A python implementation of the mosaic permutation testing framework.

Installation

To install mosaicperm, just use pip:

pip install mosaicperm

Documentation

Documentation and tutorials are available at https://mosaicperm.readthedocs.io/.

Quickstart

Below, we give a simple example showing how to use mosaicperm to test whether a set of factor exposures explain the correlations among a matrix of outcomes variables.

	import numpy as np
	import mosaicperm as mp

	# synthetic outcomes and exposures
	n_obs, n_subjects, n_factors = 100, 200, 20
	outcomes = np.random.randn(n_obs, n_subjects)
	exposures = np.random.randn(n_obs, n_subjects, n_factors)
	# example of missing data
	outcomes[0:10][:, 0:5] = np.nan
	exposures[0:10][:, 0:5] = np.nan

	# fit mosaic permutation test
	mpt = mp.factor.MosaicFactorTest(
		outcomes=outcomes,
		exposures=exposures,
		test_stat=mp.statistics.mean_maxcorr_stat,
	)
	print(mpt.fit().summary())

	# produce a time series plot of this analysis
	mpt.fit_tseries(
		nrand=100, n_timepoints=20,
	).plot_tseries()

See the documentation for more details.

Project details


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mosaicperm-0.1.1.tar.gz (23.0 kB view hashes)

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