Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
Predictive inference for singular multivariate elliptically contoured distributions
Journal of Multivariate Analysis
Linear Models and Generalizations: Least Squares and Alternatives
Linear Models and Generalizations: Least Squares and Alternatives
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In this paper, we are interested in an estimation problem concerning the mean parameter of a random matrix whose distribution is elliptically contoured. We derive two general formulas for the bias and risk functions of a class of multidimensional shrinkage-type estimators. As a by product, we generalize some recent identities established in Gaussian sample cases for which the shrinking random part is a single Kronecker-product. Here, the variance-covariance matrix of the shrinking random part is the sum of two Kronecker-products.