3 citations · 11 across the 15 of their papers we have counts for
15 papers
Test for high-dimensional linear hypothesis of mean vectors via random integration
Jianghao Li, Shizhe Hong, Zhenzhen Niu +1
In this paper, we investigate hypothesis testing for the linear combination of mean vectors across multiple populations through the method of random integration. We have establishe…
Simultaneous test of the mean vectors and covariance matrices for high-dimensional data using RMT
Zhenzhen Niu, Jianghao Li, Wenya Luo +1
In this paper, we propose a new modified likelihood ratio test (LRT) for simultaneously testing mean vectors and covariance matrices of two-sample populations in high-dimensional s…
Revised BDS Test
Wenya Luo, Zhidong Bai, Jiang Hu +1
In this paper, we focus on the BDS test, which is a nonparametric test of independence. Specifically, the null hypothesis of it is that is i.i.d. (independent a…
Test for high-dimensional mean vectors via the weighted -norm
Jianghao Li, Zhenzhen Niu, Shizhe Hong +1
In this paper, we propose a novel approach to test the equality of high-dimensional mean vectors of several populations via the weighted -norm. We establish the asymptotic nor…
Exact Separation of Eigenvalues of Large Dimensional Noncentral Sample Covariance Matrices
Zhidong Bai, Jiang Hu, Jack W. Silverstein +1
Let $ \bbB_n =\frac{1}{n}(\bbR_n + \bbT^{1/2}_n \bbX_n)(\bbR_n + \bbT^{1/2}_n \bbX_n)^* $ where $ \bbX_n $ is a matrix with independent standardized random variables…
KOO approach for scalable variable selection problem in large-dimensional regression
Zhidong Bai, Kwok Pui Choi, Yasunori Fujikoshi +1
An important issue in many multivariate regression problems is to eliminate candidate predictors with null predictor vectors. In large-dimensional (LD) setting where the numbers of…