dcorBSS: Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis

Independent component analysis based on distance correlation, including a robust variant using the bowl transformation. The package provides user-facing implementations of distance covariance and distance correlation, including memory-efficient blockwise computations for large data sets. It includes a sequential ICA estimator based on minimizing distance correlation, as well as tools for analyzing serial dependence via distance autocorrelation, dependograms, and permutation-based tests. In addition, it provides functions for testing serial dependence based on distance correlation and the Hilbert–Schmidt independence criterion. The methodology is related to Matteson and Tsay (2017) <doi:10.1080/01621459.2016.1150851> and to the robust framework of Leyder et al. (2026) <doi:10.1007/s11634-026-00674-9>.

Version:	1.0-0
Depends:	R (≥ 4.1.0)
Imports:	dccpp, dHSIC, minqa, nloptr, stats, utils, Rcpp
LinkingTo:	Rcpp
Suggests:	energy, JADE, robustbase, knitr, rmarkdown
Published:	2026-06-10
DOI:	10.32614/CRAN.package.dcorBSS (may not be active yet)
Author:	Sarah Leyder [aut], Klaus Nordhausen [aut, cre]
Maintainer:	Klaus Nordhausen <klausnordhausenR at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	yes
Materials:	ChangeLog
CRAN checks:	dcorBSS results

Documentation:

Reference manual:	dcorBSS.html , dcorBSS.pdf
Vignettes:	Getting started with dcorBSS (source, R code)

Downloads:

Package source:	dcorBSS_1.0-0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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