An asymptotically least-favorable Chernoff bound for a large class of dependent data processes

DOI10.1109/TIT.1987.1057270zbMath0625.62067MaRDI QIDQ3028128

John S. Sadowsky

Publication date: 1987

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

zbMATH Keywords

Pitman's asymptotic relative efficiencydependency structurebounded memoryless detectorsdependency contamination classexponential rate of decrease of detection error probabilitiesfinite-sample Chernoff boundsfinite-sample error probabilitiesone-shift dependency bounduniform least-favorability principleworst-case asymptotic error probability

Mathematics Subject Classification ID

Inference from stochastic processes (62M99) Detection theory in information and communication theory (94A13) Large deviations (60F10) Markov processes: hypothesis testing (62M02)

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