Add to ORKGThe iterative Stein-rule estimator and the usual estimator of the error variance are compared under the Pitman Nearness Criterion. An exact expression of Pitman's Nearness probability is derived and numerically evaluated.The iterative Stein-rule estimator and the usual estimator of the error variance are compared under the Pitman Nearness Criterion. An exact expression of Pitman's Nearness probability is derived and numerically evaluated
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
Key words and phrases: linear regression model; GPN criterion; OLS and MLE estimators; Stein estima...
In a linear regression model with proxy variables, the iterative Stein-rule estimator and the usual ...
A general method for determining Pitman Nearness is given In the case of univariate estimators. This...
計畫編號：NSC89-2118-M163-001 研究期間：200008~200107 研究經費：229,000[[abstract]]For estimating a normal variance...
[[abstract]]For estimating a normal variance under squared error loss function it is well known that...
In a multiparameter estimation problem, for first-order efficient estimators, second-order Pitman ad...
This paper presents a comparative study of the performance properties of one unbiased and two Stein-...
AbstractIn a multiparameter estimation problem, for first-order efficient estimators, second-order P...
SUMMARY. For the coefficient vector of a linear regression model with non-scalar error covariance ma...
Pitman's measure of closeness, closest estimator, Stein-type estimator, Brown-type estimator, equiva...
In a multiparameter estimation problem, for first-order efficient estimators, second-order Pitman ad...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
Key words and phrases: linear regression model; GPN criterion; OLS and MLE estimators; Stein estima...
In a linear regression model with proxy variables, the iterative Stein-rule estimator and the usual ...
A general method for determining Pitman Nearness is given In the case of univariate estimators. This...
計畫編號：NSC89-2118-M163-001 研究期間：200008~200107 研究經費：229,000[[abstract]]For estimating a normal variance...
[[abstract]]For estimating a normal variance under squared error loss function it is well known that...
In a multiparameter estimation problem, for first-order efficient estimators, second-order Pitman ad...
This paper presents a comparative study of the performance properties of one unbiased and two Stein-...
AbstractIn a multiparameter estimation problem, for first-order efficient estimators, second-order P...
SUMMARY. For the coefficient vector of a linear regression model with non-scalar error covariance ma...
Pitman's measure of closeness, closest estimator, Stein-type estimator, Brown-type estimator, equiva...
In a multiparameter estimation problem, for first-order efficient estimators, second-order Pitman ad...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
Key words and phrases: linear regression model; GPN criterion; OLS and MLE estimators; Stein estima...