pdcor
Fast and Light-Weight Partial Distance Correlation
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3 |
rolling source/ R- | pdcor_1.3.tar.gz |
3.5 KiB |
1.3 |
latest source/ R- | pdcor_1.3.tar.gz |
3.5 KiB |
1.3 |
2026-04-23 source/ R- | pdcor_1.3.tar.gz |
3.5 KiB |
1.3 |
2026-04-09 windows/windows R-4.5 | pdcor_1.3.zip |
27.3 KiB |