Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance

DOI10.1007/s11425-016-9021-6zbMath1404.62009OpenAlexW2805896465WikidataQ129732977 ScholiaQ129732977MaRDI QIDQ1989914

Yunmin Zhu, Jianxi Pan, Qingjiang Shi, Enbin Song

Publication date: 29 October 2018

Published in: Science China. Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11425-016-9021-6

zbMATH Keywords

designsaddle pointKullback-Leibler divergencemin-max problemrobust hypothesis testingleast-favorable densities

Mathematics Subject Classification ID

Robustness and adaptive procedures (parametric inference) (62F35) Measures of information, entropy (94A17) Statistical aspects of information-theoretic topics (62B10)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On general minimax theorems
• Robust Least-Squares Estimation With a Relative Entropy Constraint
• Robust techniques for signal processing: A survey
• Maximin performance of binary-input channels with uncertain noise distributions
• An Interior Point Algorithm for Large-Scale Nonlinear Programming
• Robust Hypothesis Testing With a Relative Entropy Tolerance
• Robustness and risk-sensitive filtering
• A Robust Version of the Probability Ratio Test
• Robust confidence limits
• Robust Statistics
• A trust region method based on interior point techniques for nonlinear programming.

This page was built for publication: Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance