A further study on Chen-Qin's test for two-sample Behrens-Fisher problems for high-dimensional data
DOI10.1007/s42519-021-00232-wzbMath1478.62140OpenAlexW4205972895MaRDI QIDQ2074641
Publication date: 10 February 2022
Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s42519-021-00232-w
high-dimensional data\( \chi^2\)-type mixturesthree-cumulant matched \(\chi^2\)-approximationtwo-sample Behrens-Fisher problem
Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Analysis of variance and covariance (ANOVA) (62J10)
Cites Work
- The Welch-James approximation to the distribution of the residual sum of squares in a weighted linear regression
- Two-sample Behrens-Fisher problems for high-dimensional data: a normal reference approach
- Testing the equality of several covariance matrices with fewer observations than the dimension
- Robust principal component analysis for functional data. (With comments)
- Modified Nel and van der Merwe test for the multivariate Behrens-Fisher problem.
- On error bounds for high-dimensional asymptotic distribution of \(L_2\)-type test statistic for equality of means
- Testing homogeneity of mean vectors under heteroscedasticity in high-dimension
- A two-sample test for high-dimensional data with applications to gene-set testing
- A Simple Two-Sample Test in High Dimensions Based on L2-Norm
- Analysis of Variance for Functional Data
- Approximate and Asymptotic Distributions of Chi-Squared–Type Mixtures With Applications
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