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HHG (version 1.3)

HHG-package: Heller-Heller-Gorfine Tests of Independence

Description

Heller-Heller-Gorfine (HHG) tests are a set of statistical tests of independnece between two random vectors of arbitrary dimensions given a finite sample. For testing independence between two scalar random variables, the package also contains implementations of the data-driven partitions (DDP) and all data partitions (ADP) tests which are distribution-free and thus are much faster to apply.

Arguments

Details

ll{ Package: HHG Type: Package Version: 1.3 Date: 2014-03-18 License: GPL-2 } The package contains two major functions: hhg.test and xdp.test.

References

Heller, R., Heller, Y., & Gorfine, M. (2013). A consistent multivariate test of association based on ranks of distances. Biometrika, 100(2), 503-510. Heller, R., Heller, Y., Kaufman S., & Gorfine, M. (2014). Consistent distribution-free tests of association between univariate random variables. arXiv:1308.1559.

Examples

Run this code
# See examples in the documentation for hhg.test and xdp.test.

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