Biases and mean squared errors of estimators of individual parameters are obtained for Stein type estimators of a vector parameter. It is known that for such estimators the average mean squared error over the different parameters under estimation is smaller than that for the usual unbiased estimators. However, such a property may not hold for the mean squared error of any individual estimator for the corresponding parameter. It is found that when a number of parameters are estimated simultaneously by Stein type estimators, some individual estimators have larger mean squared error than those of the usual unbiased estimators and others less. For several combinations of number of parameters and their mean and standard deviation, the range of p...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
This paper presents a comparative study of the performance properties of one unbiased and two Stein-...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
Since 1956, a large number of papers have been devoted to Stein's technique of obtaining improved es...
In this paper, the simultaneous estimation of the precision parameters of k normal distributions is ...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
The quality of a parameter estimate is usually assessed using the mean squared error (MSE). For one ...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
Stein’s result has transformed common belief in statistical world that the maximum likelihood estima...
AbstractIt is well known that the uniformly minimum variance unbiased (UMVU) estimators of the risk ...
It is well known that the uniformly minimum variance unbiased (UMVU) estimators of the risk and the ...
AbstractIn this paper, we define two restricted estimators for the regression parameters in a multip...
104 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1986.This thesis attempts to use S...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
This paper presents a comparative study of the performance properties of one unbiased and two Stein-...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
Since 1956, a large number of papers have been devoted to Stein's technique of obtaining improved es...
In this paper, the simultaneous estimation of the precision parameters of k normal distributions is ...
This paper examines the role of Stein estimation in a linear ultrastructural form of the measurement...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
The quality of a parameter estimate is usually assessed using the mean squared error (MSE). For one ...
Choosing the performance criterion to be mean squared error matrix, we have compared the least squar...
Stein’s result has transformed common belief in statistical world that the maximum likelihood estima...
AbstractIt is well known that the uniformly minimum variance unbiased (UMVU) estimators of the risk ...
It is well known that the uniformly minimum variance unbiased (UMVU) estimators of the risk and the ...
AbstractIn this paper, we define two restricted estimators for the regression parameters in a multip...
104 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1986.This thesis attempts to use S...
In this paper, we consider a linear regression model when relevant regressors are omitted in the spe...
This paper presents a comparative study of the performance properties of one unbiased and two Stein-...
253 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Much work on the James-Stein ...