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dcor: distance correlation and related E-statistics in Python.

Project description

E-statistics are functions of distances between statistical observations in metric spaces.

Distance covariance and distance correlation are dependency measures between random vectors introduced in [SRB07] with a simple E-statistic estimator.

This package offers functions for calculating several E-statistics such as:

  • Estimator of the energy distance [SR13].
  • Biased and unbiased estimators of distance covariance and distance correlation [SRB07].
  • Estimators of the partial distance covariance and partial distance covariance [SR14].

It also provides tests based on these E-statistics:

  • Test of homogeneity based on the energy distance.
  • Test of independence based on distance covariance.


[SR13]Gábor J. Székely and Maria L. Rizzo. Energy statistics: a class of statistics based on distances. Journal of Statistical Planning and Inference, 143(8):1249 – 1272, 2013. URL:, doi:10.1016/j.jspi.2013.03.018.
[SR14]Gábor J. Székely and Maria L. Rizzo. Partial distance correlation with methods for dissimilarities. The Annals of Statistics, 42(6):2382–2412, 12 2014. doi:10.1214/14-AOS1255.
[SRB07](1, 2) Gábor J. Székely, Maria L. Rizzo, and Nail K. Bakirov. Measuring and testing dependence by correlation of distances. The Annals of Statistics, 35(6):2769–2794, 12 2007. doi:10.1214/009053607000000505.

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