Fast and Light-Weight Partial Distance Correlation
Overview
Fast and memory-less computation of the partial distance correlation for vectors and matrices. Permutation-based and asymptotic hypothesis testing for zero partial distance correlation are also performed. References include: Szekely G. J. and Rizzo M. L. (2014). "Partial distance correlation with methods for dissimilarities". The Annals Statistics, 42(6): 2382--2412. doi:10.1214/14-AOS1255. Shen C., Panda S. and Vogelstein J. T. (2022). "The Chi-Square Test of Distance Correlation". Journal of Computational and Graphical Statistics, 31(1): 254--262. doi:10.1080/10618600.2021.1938585. Szekely G. J. and Rizzo M. L. (2023). "The Energy of Data and Distance Correlation". Chapman and Hall/CRC. <ISBN:9781482242744>. Kontemeniotis N., Vargiakakis R. and Tsagris M. (2025). On independence testing using the (partial) distance correlation. doi:10.48550/arXiv.2506.15659.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- NOTE12 OK, 1 NOTE2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 5includes a package overview page
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 100%
Downloads
Dependencies
Installing pdcor adds 7 packages (7 with compiled code, 3.9 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, RcppParallel 744 KB.
Code & Tests
People & History
Package metadata
- First published
- 2025-02-25
- Total releases
- 3 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.0
- Download size
- 3.5 KB
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