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Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values
Efficient estimation of finite population mean is carried out by using the auxiliary information meaningfully. In this paper we have suggested some modified ratio, product, and regression type estimators when using minimum and maximum values. Expressions for biases and mean squared errors of the sug...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3855973/ https://www.ncbi.nlm.nih.gov/pubmed/24348158 http://dx.doi.org/10.1155/2013/431868 |
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author | Khan, Manzoor Shabbir, Javid |
author_facet | Khan, Manzoor Shabbir, Javid |
author_sort | Khan, Manzoor |
collection | PubMed |
description | Efficient estimation of finite population mean is carried out by using the auxiliary information meaningfully. In this paper we have suggested some modified ratio, product, and regression type estimators when using minimum and maximum values. Expressions for biases and mean squared errors of the suggested estimators have been derived up to the first order of approximation. The performances of the suggested estimators, relative to their usual counterparts, have been studied, and improved performance has been established. The improvement in efficiency by making use of maximum and minimum values has been verified numerically. |
format | Online Article Text |
id | pubmed-3855973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38559732013-12-16 Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values Khan, Manzoor Shabbir, Javid ScientificWorldJournal Research Article Efficient estimation of finite population mean is carried out by using the auxiliary information meaningfully. In this paper we have suggested some modified ratio, product, and regression type estimators when using minimum and maximum values. Expressions for biases and mean squared errors of the suggested estimators have been derived up to the first order of approximation. The performances of the suggested estimators, relative to their usual counterparts, have been studied, and improved performance has been established. The improvement in efficiency by making use of maximum and minimum values has been verified numerically. Hindawi Publishing Corporation 2013-11-17 /pmc/articles/PMC3855973/ /pubmed/24348158 http://dx.doi.org/10.1155/2013/431868 Text en Copyright © 2013 M. Khan and J. Shabbir. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Khan, Manzoor Shabbir, Javid Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title | Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title_full | Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title_fullStr | Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title_full_unstemmed | Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title_short | Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values |
title_sort | some improved ratio, product, and regression estimators of finite population mean when using minimum and maximum values |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3855973/ https://www.ncbi.nlm.nih.gov/pubmed/24348158 http://dx.doi.org/10.1155/2013/431868 |
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