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steadyICA (version 1.0)

ICA and Tests of Independence via Multivariate Distance Covariance

Description

Functions related to multivariate measures of independence and ICA: -estimate independent components by minimizing distance covariance; -conduct a test of mutual independence based on distance covariance; -estimate independent components via infomax (a popular method but generally performs poorer than mdcovica, ProDenICA, and/or fastICA, but is useful for comparisons); -order indepedent components by skewness; -match independent components from multiple estimates; -other functions useful in ICA.

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Version

Install

install.packages('steadyICA')

Monthly Downloads

462

Version

1.0

License

GPL (>= 2)

Maintainer

Last Published

November 10th, 2015

Functions in steadyICA (1.0)

gmultidcov

Symmetric multivariate distance covariance for grouped components
rightskew

force ICs to have positive skewness and order by skewness
compInd

Complete Measure of Mutual Multivariate Independence
dcovICA

ICA via distance covariance for 2 components
permTest

Permutation test for mutual independence.
W2theta

Convert an orthogonal matrix to its angular parameterization.
multidcov

Symmetric multivariate distance covariance
dcovustat

Calculate distance covariance via U-statistics
infomaxICA

Estimates independent components via infomax
matchICA

match independent components using the Hungarian method
steadyICA

Estimate independent components by minimizing distance covariance
steadyICA-package

ICA via distance covariance, tests of mutual independence, and other ICA functions
frobICA

match mixing matrices or ICs and calculate their Frobenius distance
theta2W

Convert angles to an orthogonal matrix.
whitener

Whitening function