When population size does not matter: robust Bayesian testing for categorical populations

DOI10.1080/15598608.2011.10483738zbMath1420.62107OpenAlexW2036646917MaRDI QIDQ2324171

Mark Bauder, Sudip Bose

Publication date: 13 September 2019

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2011.10483738

zbMATH Keywords

Bayes factorBayesian robustnesslimit distributionexponential tiltingBayesian testingrobust testingmultiple populationsfinite population samplingexponential distortiontests of hypothesessrswor

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Bayesian inference (62F15) Exact distribution theory in statistics (62E15) Robustness and adaptive procedures (parametric inference) (62F35)

Cites Work

• On the effect of misspecifying the density ratio model
• On the robustness of the predictive distribution for sampling from finite populations
• Non-dependence of the predictive distribution on the population size
• A note on sampling to locate rare defectives with strong prior evidence
• A Semiparametric Approach to the One-Way Layout
• Bayesian Methods for Binomial Data with Applications to a Nonresponse Problem
• Bayesian Prediction and Population Size Assumptions
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