A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications
This study presents a novel enhanced exponential class of estimators for population mean under RSS by employing data on an auxiliary variable. The suggested estimators' mean square error (MSE) is calculated approximately at order one. The efficiency conditions that make the suggested enhanced e...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023079811 |
| _version_ | 1797646486387818496 |
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| author | M. Yusuf Najwan Alsadat Balogun Oluwafemi Samson Mahmoud Abd El Raouf Hanan Alohali |
| author_facet | M. Yusuf Najwan Alsadat Balogun Oluwafemi Samson Mahmoud Abd El Raouf Hanan Alohali |
| author_sort | M. Yusuf |
| collection | DOAJ |
| description | This study presents a novel enhanced exponential class of estimators for population mean under RSS by employing data on an auxiliary variable. The suggested estimators' mean square error (MSE) is calculated approximately at order one. The efficiency conditions that make the suggested enhanced exponential class of estimators superior to the traditional estimators are found. A simulation study using hypothetically drawn normal and exponential populations evaluates the execution of the suggested estimators. The findings demonstrate that the suggested estimators outperform their traditional equivalents. In addition, real data examples are examined to show how the proposed estimators can be implemented in various real life problems. |
| first_indexed | 2024-03-11T15:03:18Z |
| format | Article |
| id | doaj.art-fafb9d0f8330456e82aa2f9502286a1a |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-11T15:03:18Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-fafb9d0f8330456e82aa2f9502286a1a2023-10-30T06:07:20ZengElsevierHeliyon2405-84402023-10-01910e20773A novel proposed class of estimators under ranked set sampling: Simulation and diverse applicationsM. Yusuf0Najwan Alsadat1Balogun Oluwafemi Samson2Mahmoud Abd El Raouf3Hanan Alohali4Helwan University, Faculty of Science, Mathematics Department, Cairo, Egypt; Corresponding author.Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh 11587, Saudi ArabiaDepartment of Computing, Faulty of Forestry and Technology, University of Eastern Finland, FI-70211, Kuopio, FinlandBasic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, EgyptDepartment of mathematics, College of science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi ArabiaThis study presents a novel enhanced exponential class of estimators for population mean under RSS by employing data on an auxiliary variable. The suggested estimators' mean square error (MSE) is calculated approximately at order one. The efficiency conditions that make the suggested enhanced exponential class of estimators superior to the traditional estimators are found. A simulation study using hypothetically drawn normal and exponential populations evaluates the execution of the suggested estimators. The findings demonstrate that the suggested estimators outperform their traditional equivalents. In addition, real data examples are examined to show how the proposed estimators can be implemented in various real life problems.http://www.sciencedirect.com/science/article/pii/S2405844023079811Simulation studyExponential estimatorsEfficiency |
| spellingShingle | M. Yusuf Najwan Alsadat Balogun Oluwafemi Samson Mahmoud Abd El Raouf Hanan Alohali A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications Heliyon Simulation study Exponential estimators Efficiency |
| title | A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications |
| title_full | A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications |
| title_fullStr | A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications |
| title_full_unstemmed | A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications |
| title_short | A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications |
| title_sort | novel proposed class of estimators under ranked set sampling simulation and diverse applications |
| topic | Simulation study Exponential estimators Efficiency |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023079811 |
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