Two-sample high dimensional mean test based on prepivots
From MaRDI portal
Publication:2242161
DOI10.1016/j.csda.2021.107284OpenAlexW3169122735MaRDI QIDQ2242161
Deepak Nag Ayyala, Rafael Hellebuyck, Santu Ghosh
Publication date: 9 November 2021
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2003.06455
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A two sample test in high dimensional data
- Strong approximations of level exceedences related to multiple hypothesis testing
- Bivariate extreme statistics. I
- Balanced control of generalized error rates
- On the validity of the formal Edgeworth expansion
- Tail dependence for elliptically contoured distributions
- A test for the mean vector in large dimension and small samples
- A two-sample test for high-dimensional data with applications to gene-set testing
- A test for the mean vector with fewer observations than the dimension
- Asymptotically independent U-statistics in high-dimensional testing
- Non-parametric Estimation of Tail Dependence
- Analyzing Microarray Gene Expression Data
- Prepivoting Test Statistics: A Bootstrap View of Asymptotic Refinements
- Prepivoting to reduce level error of confidence sets
- On the rate of convergence of normal extremes
- The rate of convergence of extremes of stationary normal sequences
- Multivariate extremes, aggregation and dependence in elliptical distributions
- Two-Sample Test of High Dimensional Means Under Dependence
- Prepivoting composite score statistics by weighted bootstrap iteration
- A Two-Sample Test for Equality of Means in High Dimension
- An adaptive two-sample test for high-dimensional means
- The bootstrap and Edgeworth expansion
