steadyICA (version 1.0)

steadyICA-package: ICA via distance covariance, tests of mutual independence, and other ICA functions

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 steadyICA or ProDenICA but is useful for comparisons); -order independent components by skewness; -match independent components from multiple estimates; -other functions useful in ICA.

Details

ll{ Package: steadyICA Type: Package Version: 1.0 Date: 2015-11-08 License: GPL (>= 2) Depends: Rcpp (>= 0.9.13), MASS Suggests: irlba, JADE, ProDenICA, fastICA }

References

Bernaards, C. & Jennrich, R. (2005) Gradient projection algorithms and software for arbitrary rotation criteria in factor analysis. Educational and Psychological Measurement 65, 676-696

Matteson, D. S. & Tsay, R. Independent component analysis via U-Statistics.

Szekely, G., Rizzo, M. & Bakirov, N. Measuring and testing dependence by correlation of distances. (2007) The Annals of Statistics, 35, 2769-2794.

Tichavsky, P. & Koldovsky, Z. Optimal pairing of signal components separated by blind techniques. (2004) Signal Processing Letters 11, 119-122.

See Also

fastICA ProDenICA::ProDenICA

Examples

#see steadyICA