Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling
This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and compa...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024035667 |
| _version_ | 1827294045237411840 |
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| author | Mujeeb Hussain Qamruz Zaman Lakhkar Khan A.E. Metawa Fuad A. Awwad Emad A.A. Ismail Danish Wasim Hijaz Ahmad |
| author_facet | Mujeeb Hussain Qamruz Zaman Lakhkar Khan A.E. Metawa Fuad A. Awwad Emad A.A. Ismail Danish Wasim Hijaz Ahmad |
| author_sort | Mujeeb Hussain |
| collection | DOAJ |
| description | This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature. For instance, the classical [4] unbiased estimator, the estimator of [9], and other existing estimators under the explained conditions. The theoretical results are supported numerically by using real-life data sets, under the criteria of bias, mean square error, percent relative efficiency and mathematical conditions. It is also clear from the numerical results that the suggested exponential estimators performed better than the estimators in the literature. |
| first_indexed | 2024-04-24T13:50:28Z |
| format | Article |
| id | doaj.art-76e5b8057742461bbee1a67bc16ff767 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T13:50:28Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-76e5b8057742461bbee1a67bc16ff7672024-04-04T05:05:04ZengElsevierHeliyon2405-84402024-03-01106e27535Improved exponential type mean estimators for non-response case using two concomitant variables in simple random samplingMujeeb Hussain0Qamruz Zaman1Lakhkar Khan2A.E. Metawa3Fuad A. Awwad4Emad A.A. Ismail5Danish Wasim6Hijaz Ahmad7Department of Statistics, University of Peshawar, Peshawar, Pakistan; Corresponding author.Department of Statistics, University of Peshawar, Peshawar, PakistanDepartment of Statistics, Government Post Graduate College Mardan, PakistanPhysics Department, Faculty of Science, Al-Azhar University, Cairo, 11511, EgyptDepartment of Quantitative analysis, College of Business Administration, King Saud University, P.O.Box 71115, Riyadh, 11587, Saudi ArabiaDepartment of Quantitative analysis, College of Business Administration, King Saud University, P.O.Box 71115, Riyadh, 11587, Saudi ArabiaDepartment of Microbiology, Abasyn University Peshawar, PakistanSection of Mathematics, International Telematic University Uninettuno, Corso Vittorio Emanuele II, Roma, Italy; Near East University, Operational Research Center in Healthcare, Near East Boulevard, PC: 99138 Nicosia/Mersin, 10, TurkeyThis paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature. For instance, the classical [4] unbiased estimator, the estimator of [9], and other existing estimators under the explained conditions. The theoretical results are supported numerically by using real-life data sets, under the criteria of bias, mean square error, percent relative efficiency and mathematical conditions. It is also clear from the numerical results that the suggested exponential estimators performed better than the estimators in the literature.http://www.sciencedirect.com/science/article/pii/S2405844024035667ExponentialConcomitant variableNon-responseMean square error |
| spellingShingle | Mujeeb Hussain Qamruz Zaman Lakhkar Khan A.E. Metawa Fuad A. Awwad Emad A.A. Ismail Danish Wasim Hijaz Ahmad Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling Heliyon Exponential Concomitant variable Non-response Mean square error |
| title | Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling |
| title_full | Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling |
| title_fullStr | Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling |
| title_full_unstemmed | Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling |
| title_short | Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling |
| title_sort | improved exponential type mean estimators for non response case using two concomitant variables in simple random sampling |
| topic | Exponential Concomitant variable Non-response Mean square error |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024035667 |
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