dcor: distance correlation and related E-statistics in Python.
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: http://www.sciencedirect.com/science/article/pii/S0378375813000633, 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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