25 citations · 35 across the 4 of their papers we have counts for
4 papers
Direction-Projection-Permutation for High Dimensional Hypothesis Tests
Susan Wei, Chihoon Lee, Lindsay Wichers +2
Motivated by the prevalence of high dimensional low sample size datasets in modern statistical applications, we propose a general nonparametric framework, Direction-Projection-Perm…
Surprising Asymptotic Conical Structure in Critical Sample Eigen-Directions
Dan Shen, Haipeng Shen, Hongtu Zhu +1
The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal a s…
Object Oriented Data Analysis of Cell-Well Structured Data
Xiaosun Lu, J. S. Marron, Perry Haaland
Object oriented data analysis (OODA) aims at statistically analyzing populations of complicated objects. This paper is motivated by a study of cell images in cell culture biology,…
High Dimensional Principal Component Scores and Data Visualization
Dan Shen, Haipeng Shen, Hongtu Zhu +1
Principal component analysis is a useful dimension reduction and data visualization method. However, in high dimension, low sample size asymptotic contexts, where the sample size i…