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Use of an efficient unbiased estimator for finite population mean

In this study, we propose an improved unbiased estimator in estimating the finite population mean using a single auxiliary variable and rank of the auxiliary variable by adopting the Hartley-Ross procedure when some parameters of the auxiliary variable are known. Expressions for the bias and mean sq...

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Detalles Bibliográficos
Autores principales: Shabbir, Javid, Onyango, Ronald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249188/
https://www.ncbi.nlm.nih.gov/pubmed/35776700
http://dx.doi.org/10.1371/journal.pone.0270277
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author Shabbir, Javid
Onyango, Ronald
author_facet Shabbir, Javid
Onyango, Ronald
author_sort Shabbir, Javid
collection PubMed
description In this study, we propose an improved unbiased estimator in estimating the finite population mean using a single auxiliary variable and rank of the auxiliary variable by adopting the Hartley-Ross procedure when some parameters of the auxiliary variable are known. Expressions for the bias and mean square error or variance of the estimators are obtained up to the first order of approximation. Four real data sets are used to observe the performances of the estimators and to support the theoretical findings. It turns out that the proposed unbiased estimator outperforms as compared to all other considered estimators. It is also observed that using conventional measures have significant contributions in achieving the efficiency of the estimators.
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spelling pubmed-92491882022-07-02 Use of an efficient unbiased estimator for finite population mean Shabbir, Javid Onyango, Ronald PLoS One Research Article In this study, we propose an improved unbiased estimator in estimating the finite population mean using a single auxiliary variable and rank of the auxiliary variable by adopting the Hartley-Ross procedure when some parameters of the auxiliary variable are known. Expressions for the bias and mean square error or variance of the estimators are obtained up to the first order of approximation. Four real data sets are used to observe the performances of the estimators and to support the theoretical findings. It turns out that the proposed unbiased estimator outperforms as compared to all other considered estimators. It is also observed that using conventional measures have significant contributions in achieving the efficiency of the estimators. Public Library of Science 2022-07-01 /pmc/articles/PMC9249188/ /pubmed/35776700 http://dx.doi.org/10.1371/journal.pone.0270277 Text en © 2022 Shabbir, Onyango https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shabbir, Javid
Onyango, Ronald
Use of an efficient unbiased estimator for finite population mean
title Use of an efficient unbiased estimator for finite population mean
title_full Use of an efficient unbiased estimator for finite population mean
title_fullStr Use of an efficient unbiased estimator for finite population mean
title_full_unstemmed Use of an efficient unbiased estimator for finite population mean
title_short Use of an efficient unbiased estimator for finite population mean
title_sort use of an efficient unbiased estimator for finite population mean
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249188/
https://www.ncbi.nlm.nih.gov/pubmed/35776700
http://dx.doi.org/10.1371/journal.pone.0270277
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