Open AccessA Generalized Class of Estimators for Finite Population Mean Using Two Auxiliary Variables in Sample Surveys
Author(s) -
Housila P. Singh,
Pragati Nigam
Publication year - 2022
Publication title -
journal of reliability and statistical studies
Language(s) - English
Resource type - Journals
eISSN - 2229-5666
pISSN - 0974-8024
DOI - 10.13052/jrss0974-8024.1514
Subject(s) - estimator , mathematics , efficient estimator , minimum variance unbiased estimator , bias of an estimator , invariant estimator , trimmed estimator , consistent estimator , statistics , stein's unbiased risk estimate , simple random sample , extremum estimator , stratified sampling , mean squared error , ratio estimator , population , m estimator , demography , sociology
In this paper we have suggested a generalized class of estimators for estimating the finite population mean Y¯Y¯ of the study variable y using information on two auxiliary variables x and z. We have studied the properties of the proposed generalized class of estimators in simple random sampling without replacement scheme and in stratified random sampling up to the first order of approximation. It is shown that the suggested class of estimators is more efficient than the conventional unbiased estimator, ratio estimator, product estimator, traditional difference estimator, Srivastava (1967) estimator, Ray et al. (1979) estimator, Vos (1980) estimator, Upadhyaya et al. (1985) estimator, Rao (1991) estimator and Gupta and Shabbir (2008) estimator. Theoretical results are well supported through an empirical study.