Asymptotically pointwise optimal rules of sequential estimation of mean vector when an information matrix has some structure in a multivariate normal population

DOI10.1080/07474949708836394zbMath0897.62092OpenAlexW2022664295MaRDI QIDQ4368899

Hisao Nagao

Publication date: 19 October 1998

Published in: Sequential Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474949708836394

zbMATH Keywords

covariance matrixstopping ruleoptional stopping theoremasymptotically pointwise optimalmartingale convergence theoremmultivariate normal distributionA.P.O. ruleintraclass correlation structureconjugate distributionBayes stopping times

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Sequential estimation (62L12)

Related Items (2)

The risks for usual sequential estimates and stopping times of multivariate normal mean for conjugate distribution ⋮ Nondifferentiable errors in beta-compliance integrated logistic models

Cites Work

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• Bayesian sequential estimation
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• Empirical bayes methods in sequential estimation
• A.P.O. rules are asymptotically non deficient for estimation with squared error loss
• Asymptotically pointwise optimal rules for estimating the mean in general exponential dtstributions for squared loss
• On fixed width confidence regions for multivariate Normal mean when the covariance matrix Has some structure
• Some contributions to the asymptotic theory of Bayes solutions

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