Joint test for homogeneity of high-dimensional means and covariance matrices using maximum-type statistics (Q6552995)

scientific article; zbMATH DE number 7862760

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English	Joint test for homogeneity of high-dimensional means and covariance matrices using maximum-type statistics	scientific article; zbMATH DE number 7862760

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title

Joint test for homogeneity of high-dimensional means and covariance matrices using maximum-type statistics (English)

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Communications in Statistics. Simulation and Computation

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publication date

11 June 2024

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Two-sample tests for high-dimension, strongly spiked eigenvalue models

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A nonparametric two-sample test applicable to high dimensional data

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Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings

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Two-Sample Test of High Dimensional Means Under Dependence

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Simulation‐based hypothesis testing of high dimensional means under covariance heterogeneity

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Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering

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A two-sample test for high-dimensional data with applications to gene-set testing

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Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors

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Comparison and anti-concentration bounds for maxima of Gaussian random vectors

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Central limit theorems and bootstrap in high dimensions

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Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data

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A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data

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Equality tests of high-dimensional covariance matrices under the strongly spiked eigenvalue model

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Self-normalized Cramér-type large deviations for independent random variables.

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Two sample tests for high-dimensional covariance matrices

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The asymptotic distribution and Berry-Esseen bound of a new test for independence in high dimension with an application to stochastic optimization

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A Cramér moderate deviation theorem for Hotelling's \(T^{2}\)-statistic with applications to global tests

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Simultaneous testing of mean vector and covariance matrix for high-dimensional data

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Asymptotic Statistics

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Interpoint distance based two sample tests in high dimension

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Identifiers

DOI

10.1080/03610918.2022.2037641

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Mathematics Subject Classification ID

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Mathematics(1 entry)

mardi Publication:6552995