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Research Article | Open Access

Improved generalized class of estimators in estimating the finite population mean using two auxiliary variables under two-stage sampling

Sohaib Ahmad1Sardar Hussain2( )Javid Shabbir2Muhammad Aamir1M. El-Morshedy3,4Zubair Ahmad5Sharifah Alrajhi6
Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan
Department of Statistics, Quaid-i-azam University, Islamabad, Pakistan
Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt
Department of Statistics, Yazd University, P.O. Box 89175-741, Yazd, Iran
Statistics Department, Faculty of Science, King Abdul Aziz University, Jeddah, Kingdom of Saudi Arabia
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Abstract

This article addresses the problem of estimating the finite population mean using two auxiliary variables under two-stage sampling scheme. Further the proposed improved class of estimators are provided their genralized form. Mathematical properties of the existing and proposed improved generalized class of estimators are derived up to first order of approximation. We identified 11 members of the improved generalized class of estimators which are more efficient than existing estimators in terms of the percentage relative efficiency. We use two real data sets under two-stage sampling to compare the performances of all of considered estimators.

CLC number: 62D05

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AIMS Mathematics
Pages 10609-10624

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Cite this article:
Ahmad S, Hussain S, Shabbir J, et al. Improved generalized class of estimators in estimating the finite population mean using two auxiliary variables under two-stage sampling. AIMS Mathematics, 2022, 7(6): 10609-10624. https://doi.org/10.3934/math.2022592

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Received: 18 January 2022
Revised: 13 March 2022
Accepted: 24 March 2022
Published: 15 June 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)