Open AccessExponential Type Estimator for the Population Mean Under Ranked Set Sampling
Author(s) -
Khalid Ul Islam Rather,
AUTHOR_ID,
Cem Kadılar,
AUTHOR_ID
Publication year - 2021
Publication title -
journal of statistics : advances in theory and applications
Language(s) - English
Resource type - Journals
ISSN - 0975-1262
DOI - 10.18642/jsata_7100122173
Subject(s) - estimator , rss , mathematics , efficient estimator , bias of an estimator , statistics , trimmed estimator , stein's unbiased risk estimate , ratio estimator , minimum variance unbiased estimator , exponential type , exponential function , population mean , consistent estimator , invariant estimator , population , mean squared error , computer science , mathematical analysis , demography , sociology , operating system
We propose a new exponential type estimator for the population mean by adapting the estimator suggested by Kadilar [12] to the Ranked Set Sampling (RSS). Theoretically and numerically, we show that the proposed exponential type estimator is more efficient than the classical ratio estimator in the RSS and the estimator of Kadilar et al. [11].