This paper presents a general loss function under quadratic loss structure and discusses the comparison of risk functions associated with the unbiased least squares and biased Stein-rule estimators of the coefficients in a linear regression model
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
The dissertation addresses three issues in the use of Stein-like estimators of the classical normal ...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
This paper presents a general loss function under quadratic loss structure and discusses the compari...
This paper extends the balanced loss function to a more general set up. The ordinary least squares a...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
In regression analysis we are often interested in using an estimator which is "precise" and which si...
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) e...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
This article considers a linear regression model when a set of exact linear restrictions binding the...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
AbstractThis paper deals with the problem of Stein-rule prediction in a general linear model. Our st...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
The dissertation addresses three issues in the use of Stein-like estimators of the classical normal ...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
This paper presents a general loss function under quadratic loss structure and discusses the compari...
This paper extends the balanced loss function to a more general set up. The ordinary least squares a...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
In regression analysis we are often interested in using an estimator which is "precise" and which si...
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) e...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
This article considers a linear regression model when a set of exact linear restrictions binding the...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
AbstractThis paper deals with the problem of Stein-rule prediction in a general linear model. Our st...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
The dissertation addresses three issues in the use of Stein-like estimators of the classical normal ...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
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