Bayesian robustness in bidimensional models: Prior independence. (With discussion)

DOI10.1016/0378-3758(94)90118-XzbMath0805.62005OpenAlexW1977269810MaRDI QIDQ1333137

Elías Moreno, James O. Berger

Publication date: 25 January 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)90118-x

zbMATH Keywords

Bayesian robustnessepsilon contaminationindependence assumptionmultidimensional parameterdensity band classes of priorsmultivariate robustnessprior dependenceprior independencerange of posterior quantities

Mathematics Subject Classification ID

Bayesian inference (62F15) Foundations and philosophical topics in statistics (62A01)

Related Items

Robust Bayesian methodology with applications in credibility premium derivation and future claim size prediction, An overview of robust Bayesian analysis. (With discussion), Bayesian robustness of the compound Poisson distribution under bidimensional prior: an application to the collective risk model, Classes of bidimensional priors specified on a collection of sets: Bayesian robustness, Bayesian robustness on constrained density band classes, Estimating with incomplete count data: A Bayesian approach, Sets of probability distributions, independence, and convexity, Sensitivity to prior independence via farlie-gumbel-morgenstern model, On the independence between risk profiles in the compound collective risk actuarial model, Analysing the Independence Hypothesis in Models for Rare Errors: An Application to Auditing, A likelihood based robust Bayesian summary, Credal networks, Computing posterior upper expectations

Cites Work

• Unnamed Item
• Unnamed Item
• Sensitivity of some standard Bayesian estimates to prior uncertainty: A comparison
• Ranges of posterior measures for priors with unimodal contaminations
• Robust Bayes and empirical Bayes analysis with \(\epsilon\)-contaminated priors
• Bayesian inference using intervals of measures
• Linearization of Bayesian robustness problems
• Investigating therapies of potentially great benefit: ECMO. With comments and a rejoinder by the author
• Robust Bayesian analysis: sensitivity to the prior
• Ranges of Posterior Probabilities for Quasiunimodal Priors With Specified Quantiles
• Bayesian Inference with Specified Prior Marginals
• Computing Bounds on Expectations