Title: Modified exponential family for improved Searls estimation of finite population mean

Authors: S.K. Yadav; Dinesh K. Sharma; Madhulika Dube

Addresses: Department of Statistics, School of Physical and Decision Sciences, Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow-226025, UP (India) ' Department of Business, Management and Accounting, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA ' Department of Statistics, School of Physical and Decision Sciences, Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow-226025, UP, India

Abstract: This paper proposes a modified exponential ratio type (Searls, 1964) class of estimators for the estimation of population mean under simple random sampling scheme. The suggested estimator utilises the known information on highly correlated auxiliary attribute. The theoretical derivations for the bias and mean squared error for the proposed estimator are retained up to the approximation of order one and the performance properties of the estimator are compared with the well-established ratio, product, modified ratio and modified product estimators of the mean of the population for the characteristic under study. The efficiency conditions of the suggested estimator over these estimators are also obtained and the theoretical findings are verified using the empirical datasets. The efficiencies of the estimators are judged on the basis of the mean squared errors of the sampling distributions around the true population mean of the study variable.

Keywords: study variable; auxiliary attribute; exponential ratio estimator; bias; MSE; mean squared errors.

DOI: 10.1504/IJCSM.2022.127799

International Journal of Computing Science and Mathematics, 2022 Vol.16 No.2, pp.149 - 158

Received: 14 Jun 2020
Accepted: 24 Jul 2020
Published online: 19 Dec 2022 *

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