AbstractIn three or more dimensions it is well known that the usual point estimator for the mean of a multivariate normal distribution is minimax but not admissible with respect to squared Euclidean distance loss. This paper gives sufficient conditions on the prior distribution under which the Bayes estimator has strictly lower risk than the usual estimator. Examples are given for which the posterior density is useful in the formation of confidence sets
A bivariate normal distribution is considered whose mean lies in an equilateral triangle. We show by...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractEmpirical Bayes estimators are given for the mean of a k-dimensional normal distribution, k ...
AbstractIn three or more dimensions it is well known that the usual point estimator for the mean of ...
Let X have a p-dimensional normal distribution with mean vector [theta] and identity covariance matr...
Bayes estimation of the mean of a variance mixture of multivariate normal distributions is considere...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractLet X = (X1,…,Xp)t to be an observation from a p-variate normal distribution with unknown me...
PhDStatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractThe problem of minimax estimation of a multivariate normal mean vector has received much att...
In this dissertation, explicit closed form expressions are derived for the harmonic prior Bayes esti...
In this dissertation, explicit closed form expressions are derived for the harmonic prior Bayes esti...
In some invariant estimation problems under a group, the Bayes estimator against an invariant prior ...
AbstractWe construct a broad class of generalized Bayes minimax estimators of the mean of a multivar...
A bivariate normal distribution is considered whose mean lies in an equilateral triangle. We show by...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractEmpirical Bayes estimators are given for the mean of a k-dimensional normal distribution, k ...
AbstractIn three or more dimensions it is well known that the usual point estimator for the mean of ...
Let X have a p-dimensional normal distribution with mean vector [theta] and identity covariance matr...
Bayes estimation of the mean of a variance mixture of multivariate normal distributions is considere...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractLet X = (X1,…,Xp)t to be an observation from a p-variate normal distribution with unknown me...
PhDStatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractThe problem of minimax estimation of a multivariate normal mean vector has received much att...
In this dissertation, explicit closed form expressions are derived for the harmonic prior Bayes esti...
In this dissertation, explicit closed form expressions are derived for the harmonic prior Bayes esti...
In some invariant estimation problems under a group, the Bayes estimator against an invariant prior ...
AbstractWe construct a broad class of generalized Bayes minimax estimators of the mean of a multivar...
A bivariate normal distribution is considered whose mean lies in an equilateral triangle. We show by...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractEmpirical Bayes estimators are given for the mean of a k-dimensional normal distribution, k ...
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