Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK1 OK2026-06-10
Documentation
- Help pages
- 13 (1 internal)includes a package overview page
- Examples that run
- 92%11 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 85%
Downloads
Dependencies
Installing dcorBSS adds 6 packages (6 with compiled code, 5.0 MB of source tarballs). Heaviest: nloptr 2.1 MB, Rcpp 1.8 MB, RcppArmadillo 1.0 MB.
Code & Tests
People & History
- 1.0-0Latest2026-06-10 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-06-10
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 79 KB
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