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. . 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. . Szekely G. J. and Rizzo M. L. (2023). "The Energy of Data and Distance Correlation". Chapman and Hall/CRC. . Kontemeniotis N., Vargiakakis R. and Tsagris M. (2025). On independence testing using the (partial) distance correlation. .


Reference manual

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install.packages("pdcor")

1.3 by Michail Tsagris, 7 months ago


Browse source code at https://github.com/cran/pdcor


Authors: Michail Tsagris [aut, cre] , Nikolaos Kontemeniotis [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports dcov, rangen, Rfast, stats

Suggests Rfast2


Imported by estats.


See at CRAN