A novel approach for estimation Population Mean with Dual Use of in Stratified Random Sampling
This study examines a new set of estimators using stratified random sampling to estimate the finite population mean. The research forms a comprehensive class of estimators by using additional data from extremely thoroughly correlated auxiliary variables. The properties of these estimators, including...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825000870 |
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| Summary: | This study examines a new set of estimators using stratified random sampling to estimate the finite population mean. The research forms a comprehensive class of estimators by using additional data from extremely thoroughly correlated auxiliary variables. The properties of these estimators, including their biases and mean square errors, have been rigorously analyzed via numerical and simulation contemplation. As compared to the existing estimators, our suggested ones are more efficient and have a reduced minimum mean square error (MSE). These indicate that it is functioning adequately. Our proposed estimator is the most effective, according to a comparison study with other methods already in use. The results of this investigation will be useful for improving survey sampling methods in the future. |
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| ISSN: | 1110-0168 |