The aim of this study is to give the conditions, in a linear regression model with proxy variables, when is the difference of variances of two estimators getting closer to each other. One of the mentioned estimators is the iterative Stein-rule estimator (ISRE) of the disturbance variance which is obtained by taking the Stein-rule estimator of the parameters in the estimator of the disturbance variance; one is the usual ordinary least squares (OLS) estimator of the disturbance variance. For that purpose the theoretical difference of variances is derived and the numerical analysis is handled to see the pattern of given theoretical difference
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
AbstractThis paper deals with the problem of Stein-rule prediction in a general linear model. Our st...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
In a regression model with proxy variables, we consider the iterative estimator of the disturbance v...
In a linear regression model with proxy variables, the iterative Stein-rule estimator and the usual ...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
The paper investigates the effects of misspecifying the disturbances in a linear regression model as...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
This paper extends the balanced loss function to a more general set up. The ordinary least squares a...
The iterative Stein-rule estimator and the usual estimator of the error variance are compared under ...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
In this present paper, considering a linear regression model with nonspherical disturbances, improve...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
AbstractThis paper deals with the problem of Stein-rule prediction in a general linear model. Our st...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
The aim of this study is to give the conditions, in a linear regression model with proxy variables, ...
In a regression model with proxy variables, we consider the iterative estimator of the disturbance v...
In a linear regression model with proxy variables, the iterative Stein-rule estimator and the usual ...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
The paper investigates the effects of misspecifying the disturbances in a linear regression model as...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
This paper extends the balanced loss function to a more general set up. The ordinary least squares a...
The iterative Stein-rule estimator and the usual estimator of the error variance are compared under ...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
In this present paper, considering a linear regression model with nonspherical disturbances, improve...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...
AbstractThis paper deals with the problem of Stein-rule prediction in a general linear model. Our st...
The simultaneous prediction of average and actual values of study variable in a linear regression mo...