The rates of convergence of Bayes estimators in change-point analysis

DOI10.1016/0167-7152(95)00093-3zbMath0849.62018OpenAlexW2082216850MaRDI QIDQ1916213

Andrew. L. Rukhin

Publication date: 6 November 1996

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(95)00093-3

zbMATH Keywords

rates of convergenceexponential distributionsmaximum likelihood estimatorBayes estimatorlimiting distributionchange-point estimationexplicit formulazero-one loss functiongeometric prior distributionlimit of the minimum Bayes riskSpitzer's formula

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10)

Related Items (1)

Change-Point Estimation as a Nonlinear Regression Problem

Cites Work

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• Approximating the distribution of the maximum likelihood estimate of the change-point in a sequence of independent random variables
• The asymptotic behavior of some nonparametric change-point estimators
• Convergence of changepoint estimators
• Lehmann-unbiased decision rules: Admissibility and invariance
• A priori estimates in problems of ``change-points of a random sequence.
• Linear statistics in change‐point estimation and their asymptotic behaviour
• On Moment Generating Functions and Renewal Theory
• Inference about the change-point in a sequence of random variables
• A Remark on the Joint Distribution of Cumulative Sums

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