Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution
Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan
Abstract
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Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan
Abstract
Open-access reader
Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.
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Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.
Key concepts: Estimator, Shrinkage estimator, Mean squared error, Mathematics, Shrinkage, Statistics, Rayleigh distribution, Extremum estimator