HHG

R package HHG: Heller-Heller-Gorfine Tests of Independence and Equality of Distributions. 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.

Keywords for this software

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References in zbMATH (referenced in 7 articles )

Showing results 1 to 7 of 7.
Sorted by year (citations)

  1. Cui, Hengjian; Zhong, Wei: A distribution-free test of independence based on mean variance index (2019)
  2. Zhang, Kai: BET on independence (2019)
  3. Chiou, Sy Han; Qian, Jing; Mormino, Elizabeth; Betensky, Rebecca A.: Permutation tests for general dependent truncation (2018)
  4. Jin Zhu, Wenliang Pan, Wei Zheng, Xueqin Wang: Ball: An R package for detecting distribution difference and association in metric spaces (2018) arXiv
  5. Reshef, David N.; Reshef, Yakir A.; Sabeti, Pardis C.; Mitzenmacher, Michael: An empirical study of the maximal and total information coefficients and leading measures of dependence (2018)
  6. Zhao, Sihai Dave; Cai, T. Tony; Li, Hongzhe: Optimal detection of weak positive latent dependence between two sequences of multiple tests (2017)
  7. Heller, Ruth; Heller, Yair; Kaufman, Shachar; Brill, Barak; Gorfine, Malka: Consistent distribution-free (K)-sample and independence tests for univariate random variables (2016)