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We introduce hyppo, a unified library for performing multivariate hypothesis testing, including independence, two-sample, and k-sample testing.
HHG: Heller-Heller-Gorfine Tests of Independence and Equality of Distributions , 2019
Barak Brill and Shachar Kaufman · 1907
Earlier work this paper cites.
The probable error of a mean
Student · 1908
Earlier work this paper cites.
Xv.—the correlation between relatives on the supposition of mendelian inheritance
Ronald A Fisher · 1919
Earlier work this paper cites.
Multivariate analysis
Maurice S Bartlett · 1947
Earlier work this paper cites.
Modified randomization tests for nonparametric hypotheses
Meyer Dwass · 1957
Earlier work this paper cites.
Le traitement des variables vectorielles
Yves Escoufier · 1973
Earlier work this paper cites.
A unifying tool for linear multivariate statistical methods: the rv-coefficient
Paul Robert and Yves Escoufier · 1976
Earlier work this paper cites.
On a measure of lack of fit in time series models
Greta M Ljung and George EP Box · 1978
Earlier work this paper cites.
Multivariate generalizations of the wald-wolfowitz and smirnov two-sample tests
Jerome H Friedman and Lawrence C Rafsky · 1979
Earlier work this paper cites.
The generalization of student’s ratio
Harold Hotelling · 1992
Earlier work this paper cites.
Multivariate analysis of variance (manova): I. theory
Gregory Carey · 1998
Earlier work this paper cites.
Applied multivariate statistics for the social sciences. lawrence erlbaum
JP Stevens · 2002
Earlier work this paper cites.
Canonical correlation analysis: An overview with application to learning methods
David R Hardoon, Sandor Szedmak, and John Shawe-Taylor · 2004
Earlier work this paper cites.
kernlab – an S4 package for kernel methods in R
Alexandros Karatzoglou, Alex Smola, Kurt Hornik, and Achim Zeileis · 2004
Earlier work this paper cites.
Kernel methods for measuring independence
Arthur Gretton, Ralf Herbrich, Alexander Smola, Olivier Bousquet, and Bernhard Schölkopf · 2005
Earlier work this paper cites.
Permutation, parametric, and bootstrap tests of hypotheses
Phillip I Good · 2006
Earlier work this paper cites.
Measuring and testing dependence by correlation of distances
Gábor J Székely, Maria L Rizzo, and Nail K Bakirov · 2007
Cited alongside, same era.
A kernel statistical test of independence
Arthur Gretton, Kenji Fukumizu, Choon H Teo, Le Song, Bernhard Schölkopf, and Alex J Smola · 2008
Cited alongside, same era.
Brownian distance covariance
Gábor J Székely and Maria L Rizzo · 2009
Cited alongside, same era.
Consistent nonparametric tests of independence
Arthur Gretton and Györfi László · 2010
Cited alongside, same era.
Disco analysis: A nonparametric extension of analysis of variance
Maria L Rizzo, Gábor J Székely, et al · 2010
Cited alongside, same era.
A consistent multivariate test of association based on ranks of distances
Ruth Heller, Yair Heller, and Malka Gorfine · 2012
Cited alongside, same era.
Consistent distribution-free k-sample and independence tests for univariate random variables
Ruth Heller, Yair Heller, Shachar Kaufman, Barak Brill, and Malka Gorfine · 2016
Later among the works it cites.
Multivariate tests of association based on univariate tests
Ruth Heller and Yair Heller · 2016
Later among the works it cites.
Kernel mean embedding of distributions: A review and beyond
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, and Bernhard Schölkopf · 2017
Later among the works it cites.
A linear-time kernel goodness-of-fit test
Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, and Arthur Gretton · 2017
Later among the works it cites.
Kernel-based tests for joint independence
Niklas Pfister, Peter Bühlmann, Bernhard Schölkopf, and Jonas Peters · 2018
Later among the works it cites.
Fast conditional independence test for vector variables with large sample sizes
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Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Kernel-based conditional independence test and application in causal discovery
Kun Zhang, Jonas Peters, Dominik Janzing, and Bernhard Schölkopf · 2012
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Distance covariance in metric spaces
Russell Lyons · 2013
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Equivalence of distance-based and rkhs-based statistics in hypothesis testing
Dino Sejdinovic, Bharath Sriperumbudur, Arthur Gretton, and Kenji Fukumizu · 2013
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A primer on quantitized data analysis and permutation testing
Dave S Collingridge · 2013
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A primer on multivariate analysis of variance (manova) for behavioral scientists
Russell Warne · 2014
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Krzysztof Chalupka, Pietro Perona, and Frederick Eberhardt · 2018
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energy: E-Statistics: Multivariate Inference via the Energy of Data , 2018
Maria Rizzo and Gabor Szekely · 2018
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Network dependence testing via diffusion maps and distance-based correlations
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Discovering and deciphering relationships across disparate data modalities
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