An application of modified systematic sampling in auto-correlated populations

IF 1.2 4区综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES

Kuwait Journal of Science Pub Date : 2025-03-31 DOI:10.1016/j.kjs.2025.100404

Zaheen Khan , Laila A. Al-Essa , Fuad S. Al Duais , Javid Shabbir , Sat Gupta

引用次数: 0

Abstract

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.

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来源期刊

Kuwait Journal of Science MULTIDISCIPLINARY SCIENCES-

CiteScore

1.60

自引率

28.60%

发文量

132

期刊介绍： Kuwait Journal of Science (KJS) is indexed and abstracted by major publishing houses such as Chemical Abstract, Science Citation Index, Current contents, Mathematics Abstract, Micribiological Abstracts etc. KJS publishes peer-review articles in various fields of Science including Mathematics, Computer Science, Physics, Statistics, Biology, Chemistry and Earth & Environmental Sciences. In addition, it also aims to bring the results of scientific research carried out under a variety of intellectual traditions and organizations to the attention of specialized scholarly readership. As such, the publisher expects the submission of original manuscripts which contain analysis and solutions about important theoretical, empirical and normative issues.