In this paper, we derive the generalized Bayesian shrinkage estimator of parameter of Burr XII distribution under three loss functions: squared error, LINEX, and weighted balance loss functions. Therefore, we obtain three generalized Bayesian shrinkage estimators (GBSEs). In this approach, we find the posterior risk function (PRF) of the generalized Bayesian shrinkage estimator (GBSE) with respect to each loss function. The constant formula of GBSE is computed by minimizing the PRF. In special cases, we derive two new GBSEs under the weighted loss function. Finally, we give our conclusion
Burr type XII distribution plays an important role in reliability modeling, risk analyzing and proce...
In this paper, we propose to obtain the Bayesian estimators of unknown parameter of a three paramete...
We develop a new continuous distribution called the Gamma-Burr type X (GBX) distribution that extend...
The paper deals with Bayesian estimation of unknown parameters of Burr type XII distribution under t...
This paper compares the robust and E-Bayesian estimations of the shape parameter for Burr XII distri...
This study is concerned with the problem of estimating the reliability function of the parameters of...
The Burr XII distribution is one of the most important distributions in Survival analysis. In this a...
A comprehensive Bayesian analysis has been carried out in the context of informative and non-informa...
In this article, we have estimated the scale parameter of exponential distribution with a prio...
Abstract: In this paper the classical estimators of the shape parameter ș for the Burr Type XII dist...
We develop three new models from the baseline Burr type X with two parameters distribution (BX) usin...
In this paper, we obtain the point and interval estimations for a three-parameter Burr-XII distribut...
The purpose of the paper is to address the problem of estimation and prediction of the Burr type XI ...
In this paper a variety of shrinkage methods for estimating unknown population parameters has been c...
In this paper, we propose to obtain Bayesian estimators of unknown parameters of a three parameter g...
Burr type XII distribution plays an important role in reliability modeling, risk analyzing and proce...
In this paper, we propose to obtain the Bayesian estimators of unknown parameter of a three paramete...
We develop a new continuous distribution called the Gamma-Burr type X (GBX) distribution that extend...
The paper deals with Bayesian estimation of unknown parameters of Burr type XII distribution under t...
This paper compares the robust and E-Bayesian estimations of the shape parameter for Burr XII distri...
This study is concerned with the problem of estimating the reliability function of the parameters of...
The Burr XII distribution is one of the most important distributions in Survival analysis. In this a...
A comprehensive Bayesian analysis has been carried out in the context of informative and non-informa...
In this article, we have estimated the scale parameter of exponential distribution with a prio...
Abstract: In this paper the classical estimators of the shape parameter ș for the Burr Type XII dist...
We develop three new models from the baseline Burr type X with two parameters distribution (BX) usin...
In this paper, we obtain the point and interval estimations for a three-parameter Burr-XII distribut...
The purpose of the paper is to address the problem of estimation and prediction of the Burr type XI ...
In this paper a variety of shrinkage methods for estimating unknown population parameters has been c...
In this paper, we propose to obtain Bayesian estimators of unknown parameters of a three parameter g...
Burr type XII distribution plays an important role in reliability modeling, risk analyzing and proce...
In this paper, we propose to obtain the Bayesian estimators of unknown parameter of a three paramete...
We develop a new continuous distribution called the Gamma-Burr type X (GBX) distribution that extend...