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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
Author: Sarah Leyder ORCID iD [aut], Klaus Nordhausen ORCID iD [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: dcorBSS_1.0-0.zip, r-release: dcorBSS_1.0-0.zip, r-oldrel: dcorBSS_1.0-0.zip
macOS binaries: r-release (arm64): dcorBSS_1.0-0.tgz, r-oldrel (arm64): dcorBSS_1.0-0.tgz, r-release (x86_64): dcorBSS_1.0-0.tgz, r-oldrel (x86_64): dcorBSS_1.0-0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=dcorBSS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.