Adaptive testing of multiple hypotheses for stochastic processes

DOI10.1080/07362999408809374zbMath0804.62077OpenAlexW2045420689MaRDI QIDQ4314526

Andrew. L. Rukhin

Publication date: 19 January 1995

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07362999408809374

zbMATH Keywords

Gaussian processeslarge deviations principlenuisance parameternecessary and sufficient conditionmultiple hypothesesadaptive procedurelog-likelihood ratioscompact topological spaceexistence of an adaptive decision procedure

Mathematics Subject Classification ID

Bayesian problems; characterization of Bayes procedures (62C10) Robustness and adaptive procedures (parametric inference) (62F35) Non-Markovian processes: hypothesis testing (62M07) Markov processes: hypothesis testing (62M02)

Related Items (1)

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Cites Work

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• Large deviations for a general class of random vectors
• Distances and discrimination rates for stochastic processes
• Theory of statistical inference and information. Transl. from the Slovak by the author
• Gaussian measures in Banach spaces
• Large sample discrimination between two Gaussian processes with different spectra
• Distance de Hellinger-Kakutani des lois correspondant à deux processus à accroissements indépendants
• Adaptive Classification Procedures

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