On indirect estimation of small area parameters under ranked set sampling
In investigations of domains under post-stratified random sampling, it is difficult to get an acceptable precision for domain-specific estimates due to low sample sizes. Small area estimate, a popular technique that has been widely used over the past few decades, involves indirect estimating using t...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824010354 |
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| author | Shakeel Ahmed Olayan Albalawi Javid Shabbir |
| author_facet | Shakeel Ahmed Olayan Albalawi Javid Shabbir |
| author_sort | Shakeel Ahmed |
| collection | DOAJ |
| description | In investigations of domains under post-stratified random sampling, it is difficult to get an acceptable precision for domain-specific estimates due to low sample sizes. Small area estimate, a popular technique that has been widely used over the past few decades, involves indirect estimating using the auxiliary data from the entire population. In this article, we utilize a ranked set sampling (RSS) technique to achieve a greater level of precision in area-specific estimations under the assumption that ranking the smaller sets is simple, inexpensive, and flawless. RSS optimizes sample size for a fixed degree of precision or increases precision for a fixed sample size. We create direct estimators for population total under homogeneous, ratio, and regression models that are area specific. To evaluate the effectiveness and application of the suggested RSS technique, data from the Pakistan Demographic Health Survey (PDHS 2017–18) and Iris flower data are used. The effectiveness of the RSS mechanism is supported by both theoretical characteristics and Bootstrapped tests. |
| format | Article |
| id | doaj-art-99d8cbdfd5cf45c28bbda3bbfe576adc |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-99d8cbdfd5cf45c28bbda3bbfe576adc2024-11-15T06:11:22ZengElsevierAlexandria Engineering Journal1110-01682024-11-01107690697On indirect estimation of small area parameters under ranked set samplingShakeel Ahmed0Olayan Albalawi1Javid Shabbir2School of Natural Sciences, NUST, H-12 Islamabad, 44000, Pakistan; Corresponding author.Department of Statistics, Faculty of Science, University of Tabuk, Tabuk, Saudi ArabiaDepartment of Statistics University of Wah, Rawalpindi, PakistanIn investigations of domains under post-stratified random sampling, it is difficult to get an acceptable precision for domain-specific estimates due to low sample sizes. Small area estimate, a popular technique that has been widely used over the past few decades, involves indirect estimating using the auxiliary data from the entire population. In this article, we utilize a ranked set sampling (RSS) technique to achieve a greater level of precision in area-specific estimations under the assumption that ranking the smaller sets is simple, inexpensive, and flawless. RSS optimizes sample size for a fixed degree of precision or increases precision for a fixed sample size. We create direct estimators for population total under homogeneous, ratio, and regression models that are area specific. To evaluate the effectiveness and application of the suggested RSS technique, data from the Pakistan Demographic Health Survey (PDHS 2017–18) and Iris flower data are used. The effectiveness of the RSS mechanism is supported by both theoretical characteristics and Bootstrapped tests.http://www.sciencedirect.com/science/article/pii/S1110016824010354PrecisionSub-population estimationAuxiliary dataSample size |
| spellingShingle | Shakeel Ahmed Olayan Albalawi Javid Shabbir On indirect estimation of small area parameters under ranked set sampling Alexandria Engineering Journal Precision Sub-population estimation Auxiliary data Sample size |
| title | On indirect estimation of small area parameters under ranked set sampling |
| title_full | On indirect estimation of small area parameters under ranked set sampling |
| title_fullStr | On indirect estimation of small area parameters under ranked set sampling |
| title_full_unstemmed | On indirect estimation of small area parameters under ranked set sampling |
| title_short | On indirect estimation of small area parameters under ranked set sampling |
| title_sort | on indirect estimation of small area parameters under ranked set sampling |
| topic | Precision Sub-population estimation Auxiliary data Sample size |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824010354 |
| work_keys_str_mv | AT shakeelahmed onindirectestimationofsmallareaparametersunderrankedsetsampling AT olayanalbalawi onindirectestimationofsmallareaparametersunderrankedsetsampling AT javidshabbir onindirectestimationofsmallareaparametersunderrankedsetsampling |