Open AccessTwo Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution
Author(s) -
Talha Omer,
Zawar Hussain,
Muhammad Qasim,
Said Farooq Shah,
Akbar Ali Khan
Publication year - 2021
Publication title -
journal of modern applied statistical methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 28
ISSN - 1538-9472
DOI - 10.22237/jmasm/1608553440
Subject(s) - estimator , shrinkage estimator , mean squared error , mathematics , shrinkage , statistics , rayleigh distribution , extremum estimator , scale (ratio) , bias of an estimator , minimum variance unbiased estimator , m estimator , probability density function , physics , quantum mechanics
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.