Shrinkage estimator for scale parameter of gamma distribution
Gajendra K. Vishwakarma, Shubham Gupta
Abstract
Gajendra K. Vishwakarma, Shubham Gupta
Abstract
In this article, we propose a shrinkage estimator for the scale parameter of the Gamma distribution when the prior information is available and compare it with minimum mean square error (MMSE) of its usual estimator in the sense of efficiency. The proposed shrinkage estimator has smaller Mean Square Error (MSE) than MMSE estimator when the prior estimate is good. The properties of shrinkage estimator have been studied in terms of bias and mean square error. Numerical illustrations are carried out to throw light on the performance of the proposed method of estimation other conventional estimators.
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In this article, we propose a shrinkage estimator for the scale parameter of the Gamma distribution when the prior information is available and compare it with minimum mean square error (MMSE) of its usual estimator in the sense of efficiency. The proposed shrinkage estimator has smaller Mean Square Error (MSE) than MMSE estimator when the prior estimate is good. The properties of shrinkage estimator have been studied in terms of bias and mean square error. Numerical illustrations are carried out to throw light on the performance of the proposed method of estimation other conventional estimators.
Key concepts: Estimator, Shrinkage estimator, Mean squared error, Minimum mean square error, Shrinkage, Mathematics, Minimum-variance unbiased estimator, Bias of an estimator