Add to ORKGThe paper provides proofs of further important results of the dominance in quadratic loss of the 2SHI (also known as two-stage or double Stein) estimators over the usual Stein estimators in the linear regression models
In this paper, we consider a linear regression model when relevant regressors are omitted. We derive...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) e...
Key words and phrases: linear regression model; GPN criterion; OLS and MLE estimators; Stein estima...
Stein’s result has transformed common belief in statistical world that the maximum likelihood estima...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
Two stage least squares regression analysis is the most practical statistical technique that is used...
We derive simpler expressions under a certain structure of design matrices for the two-stage Aitken ...
AbstractIn a subclass of elliptical distributions, Stein estimators are robust in estimating the mea...
This thesis is concerned with the finite sample properties of some of the most widely used two-stage...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
This paper presents a general loss function under quadratic loss structure and discusses the compari...
[[abstract]]A major use of linear regression models is to predict the future. An improved shrinkage ...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
In estimation of ratio of variances in two normal distributions with unknown means, it has been show...
In this paper, we consider a linear regression model when relevant regressors are omitted. We derive...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) e...
Key words and phrases: linear regression model; GPN criterion; OLS and MLE estimators; Stein estima...
Stein’s result has transformed common belief in statistical world that the maximum likelihood estima...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
Two stage least squares regression analysis is the most practical statistical technique that is used...
We derive simpler expressions under a certain structure of design matrices for the two-stage Aitken ...
AbstractIn a subclass of elliptical distributions, Stein estimators are robust in estimating the mea...
This thesis is concerned with the finite sample properties of some of the most widely used two-stage...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
This paper presents a general loss function under quadratic loss structure and discusses the compari...
[[abstract]]A major use of linear regression models is to predict the future. An improved shrinkage ...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
In estimation of ratio of variances in two normal distributions with unknown means, it has been show...
In this paper, we consider a linear regression model when relevant regressors are omitted. We derive...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) e...