A new framework for distance and kernel-based metrics in high dimensions
Author:
Affiliation:
1. Department of Biostatistics, University of Washington
2. Department of Statistics, Texas A&M University
Publisher
Institute of Mathematical Statistics
Subject
Statistics and Probability,Statistics, Probability and Uncertainty
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Testing homogeneity in high dimensional data through random projections;Journal of Multivariate Analysis;2024-03
2. Change point detection in high dimensional data with U-statistics;TEST;2023-12-07
3. Projective independence tests in high dimensions: the curses and the cures;Biometrika;2023-11-15
4. Generalized kernel two-sample tests;Biometrika;2023-11-14
5. Statistical Inferences for Complex Dependence of Multimodal Imaging Data;Journal of the American Statistical Association;2023-05-26
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