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Nonparametric two sample testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions.
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Richard Von Mises · 1928
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Harold Hotelling · 1931
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Abraham Wald and Jacob Wolfowitz · 1940
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Jan R Magnus · 1979
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Takeaki Kariya · 1981
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Mark F Schilling · 1986
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A multivariate two-sample test based on the number of nearest neighbor type coincidences
Norbert Henze · 1988
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Topics in matrix analysis
Roger A Horn and Charles R Johnson · 1991
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Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates
Niall H Anderson, Peter Hall, and D Michael Titterington · 1994
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Effect of high dimension: by an example of a two sample problem
Zhidong D Bai and Hewa Saranadasa · 1996
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On the behrens-fisher problem: a globally convergent algorithm and a finite-sample study of the wald, lr and lm tests
Alexandre Belloni and Gustavo Didier · 2008
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A test for the two-sample problem based on empirical characteristic functions
V Alba Fernández, MD Jiménez Gamero, and J Muñoz García · 2008
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Approximation theorems of mathematical statistics , volume 162
Robert J Serfling · 2009
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Expectation of quadratic forms in normal and nonnormal variables with applications
Yong Bao and Aman Ullah · 2010
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A two-sample test for high-dimensional data with applications to gene-set testing
Song Xi Chen and Ying-Li Qin · 2010
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The spectrum of kernel random matrices
Noureddine El Karoui · 2010
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Learning with Kernels
Bernhard Schölkopf and A. J. Smola · 2002
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Nonparametric goodness-of-fit testing under Gaussian models , volume 169
Yuri Ingster and Irina A Suslina · 2003
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On a new multivariate two-sample test
L Baringhaus and C Franz · 2004
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Testing for equal distributions in high dimension
Gábor J Székely and Maria L Rizzo · 2004
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Finite sample econometrics
Aman Ullah · 2004
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An exact distribution-free test comparing two multivariate distributions based on adjacency
Paul R Rosenbaum · 2005
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B-test: A non-parametric, low variance kernel two-sample test
Wojciech Zaremba, Arthur Gretton, and Matthew Blaschko · 2010
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A more powerful two-sample test in high dimensions using random projection
Miles Lopes, Laurent Jacob, and Martin J Wainwright · 2011
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Distance covariance in metric spaces
R. Lyons · 2013
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Equivalence of distance-based and RKHS-based statistics in hypothesis testing
D. Sejdinovic, B. Sriperumbudur, A. Gretton, K. Fukumizu, et al · 2013
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A two sample test in high dimensional data
Muni S Srivastava, Shota Katayama, and Yutaka Kano · 2013
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Two-sample test of high dimensional means under dependence
Tony Cai, Weidong Liu, and Yin Xia · 2014
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Martingale limit theory and its application
Peter Hall and Christopher C Heyde · 2014
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On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions
Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, and Larry Wasserman · 2015
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On the high dimensional power of a linear-time two sample test under mean-shift alternatives
Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, and Larry Wasserman · 2015
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