AbstractThe problem of estimating the mean of a multivariate normal distribution is considered. A class of admissible minimax estimators is constructed. This class includes two well-known classes of estimators, Strawderman's and Alam's. Further, this class is much broader than theirs
Let X have a p-dimensional normal distribution with mean vector [theta] and identity covariance matr...
Let X have a p-variate normal distribution with mean vector [theta] and identity covariance matrix I...
AbstractThe paper considers estimation of matrix normal means. A class of empirical Bayes estimators...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractThe problem of estimating the mean of a multivariate normal distribution is considered. A cl...
AbstractWe investigate the problem of estimating the mean vector θ of a multivariate normal distribu...
AbstractWe construct a broad class of generalized Bayes minimax estimators of the mean of a multivar...
AbstractAssume X = (X1, …, Xp)′ is a normal mixture distribution with density w.r.t. Lebesgue measur...
AbstractLet X be a p-variate (p ≥ 3) vector normally distributed with mean μ and covariance Σ, and l...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractIn three or more dimensions it is well known that the usual point estimator for the mean of ...
AbstractIt is well known that the best equivariant estimator of the variance covariance matrix of th...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractLet X be a p-variate (p ≥ 3) vector normally distributed with mean θ and known covariance ma...
AbstractThis paper considers the problem of estimating the coefficient matrix B: m × p in a normal m...
Let X have a p-dimensional normal distribution with mean vector [theta] and identity covariance matr...
Let X have a p-variate normal distribution with mean vector [theta] and identity covariance matrix I...
AbstractThe paper considers estimation of matrix normal means. A class of empirical Bayes estimators...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractThe problem of estimating the mean of a multivariate normal distribution is considered. A cl...
AbstractWe investigate the problem of estimating the mean vector θ of a multivariate normal distribu...
AbstractWe construct a broad class of generalized Bayes minimax estimators of the mean of a multivar...
AbstractAssume X = (X1, …, Xp)′ is a normal mixture distribution with density w.r.t. Lebesgue measur...
AbstractLet X be a p-variate (p ≥ 3) vector normally distributed with mean μ and covariance Σ, and l...
AbstractWe consider estimation of a multivariate normal mean vector under sum of squared error loss....
AbstractIn three or more dimensions it is well known that the usual point estimator for the mean of ...
AbstractIt is well known that the best equivariant estimator of the variance covariance matrix of th...
AbstractBayes estimation of the mean of a variance mixture of multivariate normal distributions is c...
AbstractLet X be a p-variate (p ≥ 3) vector normally distributed with mean θ and known covariance ma...
AbstractThis paper considers the problem of estimating the coefficient matrix B: m × p in a normal m...
Let X have a p-dimensional normal distribution with mean vector [theta] and identity covariance matr...
Let X have a p-variate normal distribution with mean vector [theta] and identity covariance matrix I...
AbstractThe paper considers estimation of matrix normal means. A class of empirical Bayes estimators...