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Research Article | Open Access

A new class of ratio type estimators in single- and two-phase sampling

Amber Yousaf Dar1Nadia Saeed1Moustafa Omar Ahmed Abu-Shawiesh2( )Saman Hanif Shahbaz3Muhammad Qaiser Shahbaz3
College of Statistical and Actuarial Sciences, University of the Punjab, Lahore 54000, Pakistan
Department of Mathematics, Faculty of Science, The Hashemite University, P.O. Box 330127, Zarqa 13133, Jordan
Department of Statistics, King Abdulaziz University, Jeddah, Saudi Arabia
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Abstract

The estimation of a certain population characteristics is required for several situations. The estimates are built so that the error of estimation is minimized. In several situations estimation of the population mean is required. Different estimators for the mean are available but, there is still room for improvement. In this paper, a new class of ratio-type estimators is proposed for the estimation of the population mean. The estimators are proposed for single- and two-phase sampling schemes. The expressions for bias and mean square error are obtained for single-phase and two-phase sampling estimators. Mathematical comparison of the proposed estimators has been achieved by using some existing single-phase and two-phase sampling estimators. Extensive simulations have been conducted to compare the proposed estimators with some available single- and two-phase sampling estimators. It has been observed that the proposed estimators are better than the existing estimators. Consequently, the proposed ratio estimators are recommended for use by the practitioners in various fields of industry, engineering and medical and physical sciences.

CLC number: 62D05, 62G30, 62P99

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AIMS Mathematics
Pages 14208-14226

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Cite this article:
Dar AY, Saeed N, Abu-Shawiesh MOA, et al. A new class of ratio type estimators in single- and two-phase sampling. AIMS Mathematics, 2022, 7(8): 14208-14226. https://doi.org/10.3934/math.2022783

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Received: 02 February 2022
Revised: 12 May 2022
Accepted: 17 May 2022
Published: 15 August 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)