Asymptotics of the Minimum Sufficient Number of Observations for $d$-Guaranteed Discrimination of Two-Sided Hypotheses

DOI10.1137/S0040585X97T989817zbMath1437.62112OpenAlexW3020648500MaRDI QIDQ5107656

S. V. Simushkin, R. F. Salimov

Publication date: 28 April 2020

Published in: Theory of Probability & Its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/s0040585x97t989817

zbMATH Keywords

asymptotic analysisBayesian paradigm\(d\)-posterior approachminimal sample sizediscrimination of two hypotheses

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Bayesian inference (62F15) Causal inference from observational studies (62D20)

Cites Work

• Unnamed Item
• Confidence bounds and narrowest reliable intervals in d-posterior approach
• D-guaranteed discrimination of statistical hypotheses: a review of results and unsolved problems
• Asymptotics of the necessary sample size in testing parametric hypotheses: \(d\)-posterior approach.
• Asymptotic Statistics

This page was built for publication: Asymptotics of the Minimum Sufficient Number of Observations for $d$-Guaranteed Discrimination of Two-Sided Hypotheses