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RATIO ESTIMATION OF THE POPULATION MEAN USING AUXILIARY INFORMATION UNDER THE OPTIMAL SAMPLING DESIGN

Published online by Cambridge University Press:  11 December 2020

Chunxian Long,
Wangxue ChenOpen the ORCID record for Wangxue Chen[Opens in a new window],
Rui Yang and
Dongsen Yao
Chunxian Long
Affiliation:
Department of Mathematics and Statistics, Jishou University, Jishou 416000, China E-mail: chenwangxue2015@163.com
Wangxue Chen
Affiliation:
Department of Mathematics and Statistics, Jishou University, Jishou 416000, China E-mail: chenwangxue2015@163.com
Rui Yang
Affiliation:
Department of Mathematics and Statistics, Jishou University, Jishou 416000, China E-mail: chenwangxue2015@163.com
Dongsen Yao
Affiliation:
Department of Mathematics and Statistics, Jishou University, Jishou 416000, China E-mail: chenwangxue2015@163.com
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Abstract

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Cost-effective sampling design is a problem of major concern in some experiments especially when the measurement of the characteristic of interest is costly or painful or time-consuming. In this article, we investigate ratio-type estimators of the population mean of the study variable, involving either the first or the third quartile of the auxiliary variable, using ranked set sampling (RSS) and extreme ranked set sampling (ERSS) schemes. The properties of the estimators are obtained. The estimators in RSS and ERSS are compared to their counterparts in simple random sampling (SRS) for normal data. The numerical results show that the estimators in RSS and ERSS are significantly more efficient than their counterparts in SRS.

Keywords

auxiliary variableextreme ranked set samplingranked set samplingratio estimator

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 36 , Issue 2 , April 2022, pp. 449 - 460
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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