Enhancing mean estimators in median ranked set sampling with dual auxiliary information
When measuring the research variable is complicated, expensive, or problematic, median ranked set sampling (MRSS) is often utilized since it is straightforward to rank the components using a low-cost sorting criterion. Using this sampling scheme, many authors considered the problem of population mea...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023086358 |
| _version_ | 1797429915913551872 |
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| author | Randa Alharbi Manahil SidAhmed Mustafa Aned Al Mutairi Mohamed Hussein M. Yusuf Assem Elshenawy Said G. Nassr |
| author_facet | Randa Alharbi Manahil SidAhmed Mustafa Aned Al Mutairi Mohamed Hussein M. Yusuf Assem Elshenawy Said G. Nassr |
| author_sort | Randa Alharbi |
| collection | DOAJ |
| description | When measuring the research variable is complicated, expensive, or problematic, median ranked set sampling (MRSS) is often utilized since it is straightforward to rank the components using a low-cost sorting criterion. Using this sampling scheme, many authors considered the problem of population mean estimation with a single auxiliary variable in order to obtain more precised estimators than the traditional ratio type regression estimators. In this article, we extend their ideas based on regression approach using two auxiliary variables and introduce a new regression-type estimator along with its theoretical expression of minimum mean square error (MSE). The suggested estimator's applicability is demonstrated using both simulated and real-world data sets. |
| first_indexed | 2024-03-09T09:19:48Z |
| format | Article |
| id | doaj.art-7e0732f8568f4f4c936d7cdd0b2e3f49 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-09T09:19:48Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-7e0732f8568f4f4c936d7cdd0b2e3f492023-12-02T07:02:14ZengElsevierHeliyon2405-84402023-11-01911e21427Enhancing mean estimators in median ranked set sampling with dual auxiliary informationRanda Alharbi0Manahil SidAhmed Mustafa1Aned Al Mutairi2Mohamed Hussein3M. Yusuf4Assem Elshenawy5Said G. Nassr6Department of Statistics, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Statistics, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDepartment of Mathematics and Computer Science, Alexandria University, Alexandria 21544, EgyptDepartment of Mathematics, Faculty of Science, Helwan University, Cairo 11795, Egypt; Corresponding author.Department of Physics and Engineering Mathematics, Faculty of Engineering, Tanta University, Tanta 31733, Egypt; Mathematics and Statistics Department, College of Science, Taibah University, Yanbu, Saudi ArabiaDepartment of Statistics and Insurance, Faculty of Commerce, Arish University, Al-Arish 45511, EgyptWhen measuring the research variable is complicated, expensive, or problematic, median ranked set sampling (MRSS) is often utilized since it is straightforward to rank the components using a low-cost sorting criterion. Using this sampling scheme, many authors considered the problem of population mean estimation with a single auxiliary variable in order to obtain more precised estimators than the traditional ratio type regression estimators. In this article, we extend their ideas based on regression approach using two auxiliary variables and introduce a new regression-type estimator along with its theoretical expression of minimum mean square error (MSE). The suggested estimator's applicability is demonstrated using both simulated and real-world data sets.http://www.sciencedirect.com/science/article/pii/S2405844023086358Mean estimationRegression-type estimatorDual auxiliary informationMedian ranked set sampling |
| spellingShingle | Randa Alharbi Manahil SidAhmed Mustafa Aned Al Mutairi Mohamed Hussein M. Yusuf Assem Elshenawy Said G. Nassr Enhancing mean estimators in median ranked set sampling with dual auxiliary information Heliyon Mean estimation Regression-type estimator Dual auxiliary information Median ranked set sampling |
| title | Enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| title_full | Enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| title_fullStr | Enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| title_full_unstemmed | Enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| title_short | Enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| title_sort | enhancing mean estimators in median ranked set sampling with dual auxiliary information |
| topic | Mean estimation Regression-type estimator Dual auxiliary information Median ranked set sampling |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023086358 |
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