Estimation of the mean of a univariate normal population with unknown variance is a well-known problem in the presence of an uncertain prior information. In this study, we propose a new estimator, shrinkage pre-test estimator, which is a combination of pre-test and shrinkage estimators. The mean squared error (MSE) for the shrinkage pre-test estimator is also derived and theoretical comparisons based on MSE criterion of this new estimator with the restricted, the pre-test, and the shrinkage estimators are given. We show that the shrinkage pre-test estimator performs better than the other existing estimators. In addition, the performance of this newly proposed estimator is being assessed by conducting a simulation study. © 2010 Pakistan Jour...
In this paper, a new methodology based on the likelihood of bootstrap samples is introduced for impr...
In estimating a multivariate normal mean, both the celebrated James-Stein estimator and the Bayes es...
Shrinkage estimators incorporating homogeneous and heterogeneous minimum mean square error estimator...
The estimation of the mean of an univariate normal population with unknown variance is considered wh...
Abstract—This paper concerned with pre- test single stage shrinkage estimator for estimating the var...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean μ when a prior...
www.idescat.net/sort Some improved two-stage shrinkage testimators for the mean of normal distributi...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean µ when a prior...
Let X be a normally distributed with unknown mean µ and variance 2σ. Assume that a prior estimate 0µ...
In statistical estimation procedure prior information regarding the unknown value of parameter is ut...
In statistical estimation procedure prior information regarding the unknown value of parameter is ut...
This paper is contemplated to propose a class of shrunken estimators which is further used in constr...
This paper is contemplated to propose a class of shrunken estimators which is further used in constr...
The paper considers shrinkage estimators of the mean vector of a multivariate normal population base...
This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal d...
In this paper, a new methodology based on the likelihood of bootstrap samples is introduced for impr...
In estimating a multivariate normal mean, both the celebrated James-Stein estimator and the Bayes es...
Shrinkage estimators incorporating homogeneous and heterogeneous minimum mean square error estimator...
The estimation of the mean of an univariate normal population with unknown variance is considered wh...
Abstract—This paper concerned with pre- test single stage shrinkage estimator for estimating the var...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean μ when a prior...
www.idescat.net/sort Some improved two-stage shrinkage testimators for the mean of normal distributi...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean µ when a prior...
Let X be a normally distributed with unknown mean µ and variance 2σ. Assume that a prior estimate 0µ...
In statistical estimation procedure prior information regarding the unknown value of parameter is ut...
In statistical estimation procedure prior information regarding the unknown value of parameter is ut...
This paper is contemplated to propose a class of shrunken estimators which is further used in constr...
This paper is contemplated to propose a class of shrunken estimators which is further used in constr...
The paper considers shrinkage estimators of the mean vector of a multivariate normal population base...
This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal d...
In this paper, a new methodology based on the likelihood of bootstrap samples is introduced for impr...
In estimating a multivariate normal mean, both the celebrated James-Stein estimator and the Bayes es...
Shrinkage estimators incorporating homogeneous and heterogeneous minimum mean square error estimator...