Testing homogeneity of mean vectors under heteroscedasticity in high-dimension
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Publication:2350049
DOI10.1016/j.jmva.2015.02.005zbMath1320.62132OpenAlexW2058649730MaRDI QIDQ2350049
Takayuki Yamada, Tetsuto Himeno
Publication date: 18 June 2015
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2015.02.005
Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)
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Cites Work
- Multivariate analysis of variance with fewer observations than the dimension
- Estimations for some functions of covariance matrix in high dimension under non-normality and its applications
- A two-sample test for high-dimensional data with applications to gene-set testing
- 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
- Linear Statistical Inference and its Applications
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