Asymptotic bayesian inference in some nonstandard cases: Bernstein–von Mises Results and regular bayes' estimators

DOI10.1080/02331888708802016zbMath0617.62031OpenAlexW1987294238MaRDI QIDQ4727194

Rajesh C. Phoha

Publication date: 1987

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888708802016

zbMATH Keywords

consistencyMarkov chainsasymptotic normalityasymptotic efficiencyBernstein-von Mises theoremposterior densitymultivariate normallimiting behaviourdependent observationsconjugate families of densitiesregular Bayes estimatesregular loss functions

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Bayesian inference (62F15)

Cites Work

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• On the Bernstein-von Mises approximation of posterior distributions
• Asymptotic properties of maximum likelihood estimates in the mixed model of the analysis of variance
• Asymptotic properties of posterior distributions
• Asymptotic Properties of Maximum Likelihood Estimators in Some Nonstandard Cases, II
• Asymptotic Behavior of Statistical Estimators in the Smooth Case. I. Study of the Likelihood Ratio
• Some contributions to the asymptotic theory of Bayes solutions
• Asymptotic Properties of Maximum Likelihood Estimators in Some Nonstandard Cases
• The Bernstein-Von Mises Theorem for Markov Processes

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