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September, 1994 Estimation of a Covariance Matrix Using the Reference Prior
Ruoyong Yang, James O. Berger
Ann. Statist. 22(3): 1195-1211 (September, 1994). DOI: 10.1214/aos/1176325625


Estimation of a covariance matrix $\sum$ is a notoriously difficult problem; the standard unbiased estimator can be substantially suboptimal. We approach the problem from a noninformative prior Bayesian perspective, developing the reference noninformative prior for a covariance matrix and obtaining expressions for the resulting Bayes estimators. These expressions involve the computation of high-dimensional posterior expectations, which is done using a recent Markov chain simulation tool, the hit-and-run sampler. Frequentist risk comparisons with previously suggested estimators are also given, and determination of the accuracy of the estimators is addressed.


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Ruoyong Yang. James O. Berger. "Estimation of a Covariance Matrix Using the Reference Prior." Ann. Statist. 22 (3) 1195 - 1211, September, 1994.


Published: September, 1994
First available in Project Euclid: 11 April 2007

zbMATH: 0819.62013
MathSciNet: MR1311972
Digital Object Identifier: 10.1214/aos/1176325625

Primary: 62C10
Secondary: 62F15, 62H12

Rights: Copyright © 1994 Institute of Mathematical Statistics


Vol.22 • No. 3 • September, 1994
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