Yasir Hassan, Muhammad Farooq, Saleha Yasir, Will Murray
{"title":"On Some New Exponential Ratio Estimator of Population Mean in Two Phase Sampling","authors":"Yasir Hassan, Muhammad Farooq, Saleha Yasir, Will Murray","doi":"10.17576/jsm-2023-5207-20","DOIUrl":null,"url":null,"abstract":"In this paper, we suggest employing the exponential ratio estimator to estimate the mean of the study variable using a two-phase sample strategy with two modified auxiliary variables. Several researchers discussed the properties of the estimators they proposed and discovered that the estimators in their studies were relatively efficient. The estimators previously studied are listed chronologically in the appendix to this paper. In two phase sampling, the estimator's mean square errors and relative efficiencies are calculated using auxiliary variable information. To assess the properties of our proposed estimator, we noticed that it has a lower mean square error (MSE) than the classical ratio estimator and some other exponential ratio estimators. The estimator is more useful than other estimators in solving real-world issues, notably in engineering, environmental science, management, and biological sciences. The proposed estimator has been applied to real-world data sets such as BRICS, Son's Head Measurement, Number of Hospital Beds, Sale Price of Residence, Ambient Pressure (AP), and Heating Load. In survey research, our suggested estimator has also been demonstrated to be more effective.","PeriodicalId":21366,"journal":{"name":"Sains Malaysiana","volume":"33 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sains Malaysiana","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17576/jsm-2023-5207-20","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
In this paper, we suggest employing the exponential ratio estimator to estimate the mean of the study variable using a two-phase sample strategy with two modified auxiliary variables. Several researchers discussed the properties of the estimators they proposed and discovered that the estimators in their studies were relatively efficient. The estimators previously studied are listed chronologically in the appendix to this paper. In two phase sampling, the estimator's mean square errors and relative efficiencies are calculated using auxiliary variable information. To assess the properties of our proposed estimator, we noticed that it has a lower mean square error (MSE) than the classical ratio estimator and some other exponential ratio estimators. The estimator is more useful than other estimators in solving real-world issues, notably in engineering, environmental science, management, and biological sciences. The proposed estimator has been applied to real-world data sets such as BRICS, Son's Head Measurement, Number of Hospital Beds, Sale Price of Residence, Ambient Pressure (AP), and Heating Load. In survey research, our suggested estimator has also been demonstrated to be more effective.
在本文中,我们建议使用指数比率估计器来估计研究变量的均值,使用两个修正辅助变量的两阶段样本策略。一些研究人员讨论了他们提出的估计器的性质,并发现他们研究中的估计器是相对有效的。本文的附录按时间顺序列出了以前研究过的估计量。在两相采样中,利用辅助变量信息计算估计器的均方误差和相对效率。为了评估我们提出的估计器的性质,我们注意到它比经典的比率估计器和其他指数比率估计器具有更低的均方误差(MSE)。在解决现实世界的问题时,估计器比其他估计器更有用,特别是在工程、环境科学、管理和生物科学中。所提出的估算器已应用于现实世界的数据集,如金砖国家、Son's Head Measurement、医院病床数、住宅销售价格、环境压力(AP)和供暖负荷。在调查研究中,我们建议的估计器也被证明是更有效的。
期刊介绍:
Sains Malaysiana is a refereed journal committed to the advancement of scholarly knowledge and research findings of the several branches of science and technology. It contains articles on Earth Sciences, Health Sciences, Life Sciences, Mathematical Sciences and Physical Sciences. The journal publishes articles, reviews, and research notes whose content and approach are of interest to a wide range of scholars. Sains Malaysiana is published by the UKM Press an its autonomous Editorial Board are drawn from the Faculty of Science and Technology, Universiti Kebangsaan Malaysia. In addition, distinguished scholars from local and foreign universities are appointed to serve as advisory board members and referees.