{"title":"An Effective Estimation Strategy for Population Mean over Successive Sampling of h Occasion","authors":"A. K. Sharma, Mohd Irfan, A. K. Singh","doi":"10.1007/s40010-024-00887-7","DOIUrl":null,"url":null,"abstract":"<div><p>Two-occasion sampling might only provide a snapshot of the phenomenon under investigation. Extending to h occasions allows researchers to capture long-term trends, patterns, and changes that may emerge over time. In h-occasion successive sampling, the effective estimation of population mean is an important factor for agriculture, socioeconomic, pandemics surveys when reliable estimates are required at the h-th occasion (recent-occasion). A difference-type model of an estimator is suggested for the estimation which is escorted with the information on two auxiliary variables. The optimal estimator is the combination of the matched and unmatched sample units in the h-occasion successive sampling. Empirical studies with the competent natural mean estimator and difference type estimator based on bias and mean square errors have been demonstrated in the estimator's efficiency context. A data analysis has been conducted for the applicability to the suggested model. The approach of this work provides valuable insights into long-term trends, developmental trajectories, causal relationships, and the dynamic nature of the real-world problems.</p></div>","PeriodicalId":744,"journal":{"name":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s40010-024-00887-7","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Two-occasion sampling might only provide a snapshot of the phenomenon under investigation. Extending to h occasions allows researchers to capture long-term trends, patterns, and changes that may emerge over time. In h-occasion successive sampling, the effective estimation of population mean is an important factor for agriculture, socioeconomic, pandemics surveys when reliable estimates are required at the h-th occasion (recent-occasion). A difference-type model of an estimator is suggested for the estimation which is escorted with the information on two auxiliary variables. The optimal estimator is the combination of the matched and unmatched sample units in the h-occasion successive sampling. Empirical studies with the competent natural mean estimator and difference type estimator based on bias and mean square errors have been demonstrated in the estimator's efficiency context. A data analysis has been conducted for the applicability to the suggested model. The approach of this work provides valuable insights into long-term trends, developmental trajectories, causal relationships, and the dynamic nature of the real-world problems.
两次取样可能只能提供所调查现象的一个缩影。扩展到 h 次,研究人员就能捕捉到长期趋势、模式和可能随着时间推移而出现的变化。在 h 次连续抽样中,当需要对 h 次(最近一次)进行可靠估计时,有效估计人口平均值是农业、社会经济和流行病调查的一个重要因素。建议采用差分型估算模型进行估算,该模型由两个辅助变量的信息护航。最佳估计器是 h 次连续抽样中匹配和非匹配样本单位的组合。基于偏差和均方误差的自然平均估算器和差分估算器的实证研究证明了估算器的效率。还对建议模型的适用性进行了数据分析。这项工作的方法为了解长期趋势、发展轨迹、因果关系和现实世界问题的动态性质提供了宝贵的见解。