Shachar Kaufman, based in part on an earlier implementation by Ruth Heller and Yair Heller.
Heller-Heller-Gorfine (HHG) tests are a set of statistical tests of independence between two random vectors of arbitrary dimensions. For the case of testing independence between random variables (rather than vectors), the package also offers implementations of the DDP and ADP tests which are consistent against all continuous alternatives but are distribution-free, and thus much faster to apply.

Heller-Heller-Gorfine (HHG) tests are a set of powerful statistical tests of independence between two random vectors of arbitrary dimensions. For the case of testing independence between random variables (rather than vectors), the package also offers implementations of the DDP and ADP tests, which are consistent against all continuous alternatives but are distribution-free and thus much faster to apply.

Heller-Heller-Gorfine Tests of Independence and Equality of
Distributions
Barak Brill & Shachar Kaufman, based in part on an earlier implementation by Ruth Heller and Yair Heller.
Heller-Heller-Gorfine (HHG) tests are a set of powerful statistical tests of multivariate k-sample homogeneity and independence. For the univariate case, the package also offers implementations of the MinP DDP and MinP ADP tests, which are consistent against all continuous alternatives but are distribution-free, and are thus much faster to apply.

Barak Brill & Shachar Kaufman, based in part on an earlier
implementation by Ruth Heller and Yair Heller.
Heller-Heller-Gorfine ('HHG') tests are a set of powerful statistical
tests of multivariate k-sample homogeneity and independence. For the univariate
case, the package also offers implementations of the 'MinP DDP' and 'MinP ADP'
tests, which are consistent against all continuous alternatives but are
distribution-free, and are thus much faster to apply.

Heller-Heller-Gorfine tests are a set of powerful statistical
tests of multivariate k-sample homogeneity and independence (Heller et. al., 2013, <doi:10.1093/biomet/ass070>). For the univariate
case, the package also offers implementations of the 'MinP DDP' and 'MinP ADP'
tests by Heller et. al. (2016), which are consistent against all continuous alternatives but are
distribution-free, and are thus much faster to apply.