{"title":"分层双抽样下总体均值的多变量比率指数估计","authors":"Siraj Muneer, A. Khalil, J. Shabbir","doi":"10.1080/08898480.2022.2055870","DOIUrl":null,"url":null,"abstract":"ABSTRACT To estimate the population mean when sampling a heterogeneous population and in the absence of a priori information on auxiliary variables, exponential-ratio multivariate estimators are associated under double stratified sampling with two auxiliary variables. Their biases and mean square errors are expressed and simulated. These mean square errors are smaller (the efficiencies are higher) than those of the sample mean estimator and those of other ratio estimators when the correlation between the study and the auxiliary variables exceeds 0.1 in absolute value. In particular, the proposed estimators are more efficient for low correlations between the study and the auxiliary variables. The gain in efficiency reaches a factor of 230.4% on an empirical dataset where the study variable is weakly correlated with each of the two auxiliary variables, and 182.1% on another empirical dataset where it is strongly correlated.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"30 1","pages":"122 - 141"},"PeriodicalIF":1.4000,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multivariate ratio exponential estimators of the population mean under stratified double sampling\",\"authors\":\"Siraj Muneer, A. Khalil, J. Shabbir\",\"doi\":\"10.1080/08898480.2022.2055870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT To estimate the population mean when sampling a heterogeneous population and in the absence of a priori information on auxiliary variables, exponential-ratio multivariate estimators are associated under double stratified sampling with two auxiliary variables. Their biases and mean square errors are expressed and simulated. These mean square errors are smaller (the efficiencies are higher) than those of the sample mean estimator and those of other ratio estimators when the correlation between the study and the auxiliary variables exceeds 0.1 in absolute value. In particular, the proposed estimators are more efficient for low correlations between the study and the auxiliary variables. The gain in efficiency reaches a factor of 230.4% on an empirical dataset where the study variable is weakly correlated with each of the two auxiliary variables, and 182.1% on another empirical dataset where it is strongly correlated.\",\"PeriodicalId\":49859,\"journal\":{\"name\":\"Mathematical Population Studies\",\"volume\":\"30 1\",\"pages\":\"122 - 141\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Population Studies\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/08898480.2022.2055870\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Population Studies","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/08898480.2022.2055870","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Multivariate ratio exponential estimators of the population mean under stratified double sampling
ABSTRACT To estimate the population mean when sampling a heterogeneous population and in the absence of a priori information on auxiliary variables, exponential-ratio multivariate estimators are associated under double stratified sampling with two auxiliary variables. Their biases and mean square errors are expressed and simulated. These mean square errors are smaller (the efficiencies are higher) than those of the sample mean estimator and those of other ratio estimators when the correlation between the study and the auxiliary variables exceeds 0.1 in absolute value. In particular, the proposed estimators are more efficient for low correlations between the study and the auxiliary variables. The gain in efficiency reaches a factor of 230.4% on an empirical dataset where the study variable is weakly correlated with each of the two auxiliary variables, and 182.1% on another empirical dataset where it is strongly correlated.
期刊介绍:
Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions.
The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.