39 citations · 41 across the 5 of their papers we have counts for
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stat.ME2026
Adaptable Regularized CCA Tests for Independence of High-Dimensional Random Vectors
Haoran Li
We propose an adaptable testing procedure for independence between two high-dimensional random vectors. The method incorporates ridge regularization and principal component-based d…
stat.ME2018★ 2 cited
High-dimensional general linear hypothesis tests via non-linear spectral shrinkage
Haoran Li, Alexander Aue, Debashis Paul
We are interested in testing general linear hypotheses in a high-dimensional multivariate linear regression model. The framework includes many well-studied problems such as two-sam…
stat.ME2016★ 39 cited
An adaptable generalization of Hotelling's test in high dimension
Haoran Li, Alexander Aue, Debashis Paul +2
We propose a two-sample test for detecting the difference between mean vectors in a high-dimensional regime based on a ridge-regularized Hotelling's . To choose the regulariza…