A modified generalized class of exponential ratio type estimators in ranked set sampling
| dc.contributor.author | Adesina, Olumide Sunday | |
| dc.date.accessioned | 2024-02-13T09:28:10Z | |
| dc.date.available | 2024-02-13T09:28:10Z | |
| dc.date.issued | 2023-03-22 | |
| dc.description.abstract | Background: Researchers consider ranked set sampling (RSS) as an alternative to simple random sampling (SRS) for data collection because studies have shown that it is more efficient and less biased. Also, introducing population parameters to estimators increases the efficiency of such estimators. Aim: This study derived a modified generalized class of exponential ratio estimator in RSS by introducing available population parameters and compared the results with an existing version in SRS. Methodology: The biases and mean square errors (MSE) of the proposed estimators were derived up to the terms of first-order approximation using Taylor’s series expansion. Efficiency was used as the mode of comparison between the proposed and existing estimators. Results: Life data sets and simulated data supported the numerical illustration to corroborate the theoretical results. Conclusion: The MSEs of the modified generalized class of estimators under RSS were found to be smaller than those of the existing generalized class of estimators under SRS; hence they are more efficient estimators. | |
| dc.identifier.uri | https://doi.org/10.1016/j.sciaf.2022.e01447 | |
| dc.identifier.uri | https://repository.run.edu.ng/handle/123456789/3893 | |
| dc.language.iso | en | |
| dc.publisher | Scientific African | |
| dc.relation.ispartofseries | Vol. 19 | |
| dc.title | A modified generalized class of exponential ratio type estimators in ranked set sampling | |
| dc.type | Article |