Add to ORKG16 pages, 1 article*Shrinkage Estimators Under Spherically Symmetry for the General Linear Model with respect to General Quadratic Loss* (Cellier, Dominique; Fourdrinier, Dominique) 16 page
AbstractWe study the degrees of freedom in shrinkage estimation of regression coefficients. Generali...
AbstractWhen estimating, under quadratic loss, the location parameterθof a spherically symmetric dis...
AbstractConsider the problem of estimating the mean vector θ of a random variable X in Rp, with a sp...
AbstractThis paper is primarily concerned with extending the results of Brandwein and Strawderman in...
This book provides a coherent framework for understanding shrinkage estimation in statistics. The te...
The subject of this master thesis is shrinkage estimators for the location parameter of an elliptica...
The subject of this master thesis is shrinkage estimators for the location parameter of an elliptica...
The dissertation considers three different topics which pertain to minimax shrinkage estimation: 1)...
Abstract Parameter estimation in multivariate analysis is important, particularly when parameter spa...
This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal d...
Consider the problem of estimating the mean vector [theta] of a random variable X in , with a spheri...
AbstractThe estimation of the location parameter of a spherically symmetric distribution was greatly...
AbstractTn the normal case it is well known that, although the James-Stein rule is minimax, it is no...
AbstractTn the normal case it is well known that, although the James-Stein rule is minimax, it is no...
We study the degrees of freedom in shrinkage estimation of regression coefficients. Generalizing the...
AbstractWe study the degrees of freedom in shrinkage estimation of regression coefficients. Generali...
AbstractWhen estimating, under quadratic loss, the location parameterθof a spherically symmetric dis...
AbstractConsider the problem of estimating the mean vector θ of a random variable X in Rp, with a sp...
AbstractThis paper is primarily concerned with extending the results of Brandwein and Strawderman in...
This book provides a coherent framework for understanding shrinkage estimation in statistics. The te...
The subject of this master thesis is shrinkage estimators for the location parameter of an elliptica...
The subject of this master thesis is shrinkage estimators for the location parameter of an elliptica...
The dissertation considers three different topics which pertain to minimax shrinkage estimation: 1)...
Abstract Parameter estimation in multivariate analysis is important, particularly when parameter spa...
This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal d...
Consider the problem of estimating the mean vector [theta] of a random variable X in , with a spheri...
AbstractThe estimation of the location parameter of a spherically symmetric distribution was greatly...
AbstractTn the normal case it is well known that, although the James-Stein rule is minimax, it is no...
AbstractTn the normal case it is well known that, although the James-Stein rule is minimax, it is no...
We study the degrees of freedom in shrinkage estimation of regression coefficients. Generalizing the...
AbstractWe study the degrees of freedom in shrinkage estimation of regression coefficients. Generali...
AbstractWhen estimating, under quadratic loss, the location parameterθof a spherically symmetric dis...
AbstractConsider the problem of estimating the mean vector θ of a random variable X in Rp, with a sp...