Multiple Comparisons Among Mean Vectors When the Dimension is Larger Than the Total Sample Size

DOI10.1080/03610918.2012.762387zbMath1328.62476OpenAlexW2035617787MaRDI QIDQ2876145

Takahiro Nishiyama, Masashi Hyodo, Sho Takahashi

Publication date: 18 August 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.762387

zbMATH Keywords

asymptotic expansionMonte Carlo simulationhigh-dimensional datacomparisons with a controlBonferroni's inequalitypairwise comparisonsDempster trace criterion

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Paired and multiple comparisons; multiple testing (62J15)

Related Items (11)

A high-dimensional test on linear hypothesis of means under a low-dimensional factor model ⋮ Testing linear hypotheses of mean vectors for high-dimension data with unequal covariance matrices ⋮ Normalizing transformation of Dempster type statistic in high-dimensional settings ⋮ Unnamed Item ⋮ Accurate inference for repeated measures in high dimensions ⋮ On error bounds for high-dimensional asymptotic distribution of \(L_2\)-type test statistic for equality of means ⋮ Tests for parallelism and flatness hypotheses of two mean vectors in high-dimensional settings ⋮ A one-sample location test based on weighted averaging of two test statistics when the dimension and the sample size are large ⋮ On Test Statistics in Profile Analysis with High-dimensional Data ⋮ An exact method for the multiple comparison of several polynomial regression models with applications in dose-response study ⋮ Multiple Comparisons Among Mean Vectors When the Dimension is Larger Than the Total Sample Size

Cites Work

• The extreme value of the generalized distances of the individual points in the multivariate normal sample
• Testing the equality of several covariance matrices with fewer observations than the dimension
• Multiple Comparisons Among Mean Vectors When the Dimension is Larger Than the Total Sample Size
• Asymptotic Results of a High Dimensional MANOVA Test and Power Comparison When the Dimension is Large Compared to the Sample Size
• A Significance Test for the Separation of Two Highly Multivariate Small Samples
• A High Dimensional Two Sample Significance Test

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