Title: New family of estimators for population mean using regression-cum-ratio exponential estimators

Authors: S.K. Yadav; Cem Kadilar; Dinesh K. Sharma

Addresses: Department of Statistics, Babasaheb Bhimrao Ambedkar University, Lucknow-226025, India ' Department of Statistics, Hacettepe University, Beytepe, Ankara, Turkey ' Department of Business, Management and Accounting, University of Maryland Eastern Shore, Princess Anne, Maryland-21853, USA

Abstract: Sampling is inevitable whenever the population is vast, and one estimates the population mean rather than to calculate it. This article improves the estimation for the population mean of the primary variable through a new ratio-cum-exponential ratio family of estimators. The estimation properties, mainly bias and mean squared errors (MSE), are studied up to an approximation of order one for the suggested family. We make a comparison of the suggested family of estimators with the existing competing estimators of the population mean of the main variable in theory. In this way, the efficiency conditions for the suggested family are obtained. These conditions are satisfied in practice using the numerical example.

Keywords: main variable; supplementary variable; ratio-cum-exponential estimators; bias; mean squared errors; MSE; efficiency.

DOI: 10.1504/IJMOR.2021.112271

International Journal of Mathematics in Operational Research, 2021 Vol.18 No.1, pp.85 - 114

Received: 28 Jun 2019
Accepted: 09 Aug 2019
Published online: 06 Jan 2021 *

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