A two sample test in high dimensional data

By Muni S. Srivastava, Shota Katayama, Yutaka Kano. 2013

149 citations recorded by the source corpus.

Subfields: Applied Mathematics, Artificial Intelligence, Statistics and Probability

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Citations in the corpus

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing (2015, background): “Srivastava and Du [2008] and Srivastava et al. [2013] proposed to instead use diag( S ) − 1 instead of S − 1 , in T H , and showed its advantages in certain settings over T BS (speciﬁcally its scale invariance, i.e. invariance when the data is rescaled by a diagonal matrix, gives it an advantage…”
Classification Accuracy as a Proxy for Two Sample Testing (2016, background): “Assumption (A3) rules out highly imbalanced cases and is common in the two-sample literature (e.g. Bai and Saranadasa, 1996; Chen and Qin, 2010; Srivastava et al., 2013).”
A Simple Two-Sample Test in High Dimensions Based on L2-Norm (2020, methodology): “Such a covariance matrix was also used by Srivastava, Katayama, and Kano (2013) and Yamada and Himeno (2015).”
Two-sample tests for high-dimension, strongly spiked eigenvalue models (2016, methodology): “We used computer simulations to study the performance of the test procedure given by (3.1) when Katayama and Kano (2013) considered a test procedure given by T ( A ⋆ ( d ) ).”
On testing the equality of high dimensional mean vectors with unequal covariance matrices (2014, background): “…high dimensional tests have been proposed by Bai and Saranadasa (1996), Fujikoshi et al. (2004), Srivastava and Fujikoshi (2006), Srivastava (2007), Schott (2007), Srivastava and Du (2008), Srivastava (2009), Srivastava and Yanagihara (2010), Chen and Qin (2010) and Srivastava et al. (2011, 2013).”
TWO-SAMPLE BEHRENS-FISHER PROBLEM FOR HIGH-DIMENSIONAL DATA (2015, methodology): “Because both the two ratios are higher than the acceptable level, the empirical sizes of the test statistics proposed by Srivastava et al. (2013) will also deviate from the significance level.”
Multivariate-Sign-Based High-Dimensional Tests for the Two-Sample Location Problem (2016, methodology): “Next, we consider the high-dimensional cases, p > n, and compare the SS with the tests proposed by Chen and Qin (2010) (CQ), Srivastava, Katayama, and Kano (2013) (SKK), and Gregory et al. (2014) (GCT).”