An application of modified systematic sampling in auto-correlated populations
This study explores the efficiency of modified systematic sampling (MSS) in the context of auto-correlated populations. The MSS scheme is compared to linear systematic sampling (LSS), circular systematic sampling (CSS) and mixed random systematic sampling (MRSS) under different superpopulation models, emphasizing its applicability to auto-correlated datasets. Through numerical simulations and empirical validations, MSS demonstrates superior efficiency over conventional methods, making it a promising approach for various fields dealing with auto-correlated data. © 2025 The Authors
Authors
- Laila A. Al‐Essa (ORCID: https://orcid.org/0000-0003-2788-8946)
- Zaheen Khan (ORCID: https://orcid.org/0000-0003-3976-828X)
- Javid Shabbir (ORCID: https://orcid.org/0000-0002-0035-7072)
- Sat Gupta (ORCID: https://orcid.org/0000-0002-3661-9329)
- Fuad S. Al Duais
Publication Details
- Journal
- Kuwait Journal of Science
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1016/j.kjs.2025.100404
- Citations
- 1
- Primary Topic
- Survey Sampling and Estimation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.63