High-Dimension, Low–Sample Size Perspectives in Constrained Statistical Inference

DOI10.1198/016214507000000077zbMath1172.62335OpenAlexW1970943303MaRDI QIDQ5307669

Yuh-Shan Jou, Pranab Kumar Sen, Ming-Tien Tsai

Publication date: 18 September 2007

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/016214507000000077

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (7)

Kendall's tau-type rank statistics in genome data. ⋮ Union-intersection principle and constrained statistical inference ⋮ Bivariate high-level exceedance and the Chen-Stein theorem in genomics multiple hypothesis testing perspectives ⋮ Burden of bioinformatics in medical research: statistical perspectives and controversies ⋮ Entropy based constrained inference for some HDLSS genomic models: UI tests in a Chen-Stein perspective ⋮ Decomposability of high-dimensional diversity measures: quasi-\(U\)-statistics, martingales and nonstandard asymptotics ⋮ Two-Stage Procedures for High-Dimensional Data

This page was built for publication: High-Dimension, Low–Sample Size Perspectives in Constrained Statistical Inference