In statistical estimation procedure prior information regarding the unknown value of parameter is utilizing and it may result in a decrease of sampling variability of the estimator or it may save sample size which is desirable in many estimation procedures. The commonly used approaches in statistical inference which utilize prior information are Bayesian approach, preliminary test procedure and shrinkage estimation. The paper proposes preliminary test estimator and shrinkage preliminary test estimator for the variance in normal distribution and studies its property under Linex loss function. The paper also proposes and suggests shrinkage preliminary test estimator for the variance in negative exponential distribution and studies its propert...
In this article, the preliminary test estimator is considered under the BLINEX loss func-tion. The p...
In this paper a variety of shrinkage methods for estimating unknown population parameters has been c...
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...
We considered estimation of the parameters of the exponential distribution based on record data in t...
Estimation of the mean of a univariate normal population with unknown variance is a well-known probl...
In this article, we have estimated the scale parameter of exponential distribution with a prio...
This paper considers the preliminary test estimator of the unknown parameter of the exponential dist...
We considered estimation of the parameters of the exponential distribution based on record data in t...
A preliminary test approach using shrinkage technique is proposed for the estimation of a Poisson pa...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean µ when a prior...
Abstract—This paper concerned with pre- test single stage shrinkage estimator for estimating the var...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean μ when a prior...
A variety of shrinkage methods for estimating unknown parameters has been considered. We derive and ...
In this article, the preliminary test estimator is considered under the BLINEX loss func-tion. The p...
In this paper a variety of shrinkage methods for estimating unknown population parameters has been c...
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...
We considered estimation of the parameters of the exponential distribution based on record data in t...
Estimation of the mean of a univariate normal population with unknown variance is a well-known probl...
In this article, we have estimated the scale parameter of exponential distribution with a prio...
This paper considers the preliminary test estimator of the unknown parameter of the exponential dist...
We considered estimation of the parameters of the exponential distribution based on record data in t...
A preliminary test approach using shrinkage technique is proposed for the estimation of a Poisson pa...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean µ when a prior...
Abstract—This paper concerned with pre- test single stage shrinkage estimator for estimating the var...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
In this paper, we introduced some two-stage shrinkage testimators (TSST) for the mean μ when a prior...
A variety of shrinkage methods for estimating unknown parameters has been considered. We derive and ...
In this article, the preliminary test estimator is considered under the BLINEX loss func-tion. The p...
In this paper a variety of shrinkage methods for estimating unknown population parameters has been c...
Let X be a normally distributed with unknown mean µ and variance 2σ. Assume that a prior estimate 0µ...