Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis R package dcorBSS version 1.0-0 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>. Software Depends: R (>= 4.1.0) Imports: dccpp, dHSIC, minqa, nloptr, stats, utils, Rcpp LinkingTo: Rcpp Suggests: energy, JADE, robustbase, knitr, rmarkdown Klaus Nordhausen <klausnordhausenR@gmail.com> Comprehensive R Archive Network (CRAN) Sarah Leyder [aut] (ORCID: <https://orcid.org/0000-0002-0828-0399>), Klaus Nordhausen [aut, cre] (ORCID: <https://orcid.org/0000-0002-3758-8501>) GPL (>= 3) 2026-06-10 application/tgz https://CRAN.R-project.org/package=dcorBSS doi:10.32614/CRAN.package.dcorBSS