Distances and discrimination rates for stochastic processes

DOI10.1016/0304-4149(90)90121-8zbMath0701.62084OpenAlexW2001392448MaRDI QIDQ914309

Igor Vajda

Publication date: 1990

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

Full work available at URL: https://doi.org/10.1016/0304-4149(90)90121-8

zbMATH Keywords

diffusion processesHellinger integralsMarkov kernelsconvex distancesdistributions of regular Markov processesFisher informationsfunctional propertiesKullback- Leibler divergencesmixed error of Bayes testsRate of discriminationRényi distancessecond kind error of Neyman-Pearson tests

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical aspects of information-theoretic topics (62B10) Asymptotic properties of parametric tests (62F05) Markov processes: hypothesis testing (62M02)

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Optimal statistical decisions about some alternative financial models ⋮ Adaptive decision making for stochastic processes ⋮ Sensitivity analysis for rare events based on Rényi divergence ⋮ Adaptive testing of multiple hypotheses for stochastic processes ⋮ Minimal Kullback–Leibler Divergence for Constrained Lévy–Itô Processes ⋮ Adaptive tests for stochastic processes in the ergodic case ⋮ Unnamed Item ⋮ Unnamed Item

Cites Work

• Topics in statistical information theory
• Theory of statistical inference and information. Transl. from the Slovak by the author
• Distance de Hellinger-Kakutani des lois correspondant à deux processus à accroissements indépendants
• Chernoff bounds for discriminating between two markov processes
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