An Efficient Poisson-Distributed Adaptive Cluster Sampling Model Using Randomized Response Strategy
| dc.contributor.author | Adesina, Olumide Sunday | |
| dc.date.accessioned | 2025-04-03T15:15:27Z | |
| dc.date.available | 2025-04-03T15:15:27Z | |
| dc.date.issued | 2024-08 | |
| dc.description.abstract | The key innovation lies in the incorporation of an adaptive cluster sampling strategy and a randomized response model based on the Poisson distribution. This integration aims to overcome shortcomings inherent in conventional models, providing a more robust framework for research area. In this paper, an adaptive cluster sampling randomized response model with Poisson distribution using a randomized response strategy was proposed. The proposed cluster randomized response model has improved efficiency and a large gain in precision. Conditions were obtained under which the proposed model is more efficient than the existing models. To validate the effectiveness of our approach, numerical computations were conducted, offering concrete illustrations of the model's performance. The results underscore the significant gains in efficiency and precision achieved by the proposed adaptive cluster sampling randomized response model. | |
| dc.identifier.uri | 10.18280/isi.290407 | |
| dc.identifier.uri | https://repository.run.edu.ng/handle/123456789/4250 | |
| dc.language.iso | en | |
| dc.publisher | IIETA | |
| dc.relation.ispartofseries | Vol. 29; No. 4 | |
| dc.title | An Efficient Poisson-Distributed Adaptive Cluster Sampling Model Using Randomized Response Strategy | |
| dc.type | Article |