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\iteman{ZMATH 06130705}
\itemau{Bouriga, M.; F\'eron, O.}
\itemti{Estimation of covariance matrices based on hierarchical inverse-Wishart priors.}
\itemso{J. Stat. Plann. Inference 143, No. 4, 795-808 (2013).}
\itemab
Summary: This paper focuses on Bayesian shrinkage methods for covariance matrix estimation. We examine posterior properties and frequentist risks of Bayesian estimators based on new hierarchical inverse-Wishart priors. More precisely, we give the conditions for the existence of the posterior distributions. Advantages in terms of numerical simulations of posteriors are shown. A simulation study illustrates the performance of the estimation procedures under three loss functions for relevant sample sizes and various covariance structures.
\itemrv{~}
\itemcc{62}
\itemut{Bayesian covariance estimation; skrinkage; hierarchical inverse-Wishart prior; loss function; experiments comparisons}
\itemli{doi:10.1016/j.jspi.2012.09.006}
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