{"title":"分层排序集样本总体均值的广义修正比积类指数估计","authors":"Rikan A. Ahmed, Saja Mohammad Hussein","doi":"10.22075/IJNAA.2022.5657","DOIUrl":null,"url":null,"abstract":"In this study, we present a proposal aimed at estimating the finite population's mean of the main variable by stratification rank set sample (S_{t}text{RSS}) through the modification made to generalized ratio-cum-product type exponential estimator. The relative bias (text{PRB}), Mean Squared Error (text{Mse}) and percentage relative efficiencies (text{PRE}) of the proposed modified estimator is obtained to the first degree of approximation. Conditions under which the proposed estimator is more efficient than the usual unbiased estimator, ratio, product type estimators, and some other estimators are obtained. Finally, the estimators' abilities are evaluated through the use of simulations, as showed that the proposed modified estimator is more efficient as compared to several other estimators.","PeriodicalId":14240,"journal":{"name":"International Journal of Nonlinear Analysis and Applications","volume":"13 1","pages":"1137-1149"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Generalized modified ratio-cum-product kind exponentially estimator of the populations mean in stratified ranked set sample\",\"authors\":\"Rikan A. Ahmed, Saja Mohammad Hussein\",\"doi\":\"10.22075/IJNAA.2022.5657\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we present a proposal aimed at estimating the finite population's mean of the main variable by stratification rank set sample (S_{t}text{RSS}) through the modification made to generalized ratio-cum-product type exponential estimator. The relative bias (text{PRB}), Mean Squared Error (text{Mse}) and percentage relative efficiencies (text{PRE}) of the proposed modified estimator is obtained to the first degree of approximation. Conditions under which the proposed estimator is more efficient than the usual unbiased estimator, ratio, product type estimators, and some other estimators are obtained. Finally, the estimators' abilities are evaluated through the use of simulations, as showed that the proposed modified estimator is more efficient as compared to several other estimators.\",\"PeriodicalId\":14240,\"journal\":{\"name\":\"International Journal of Nonlinear Analysis and Applications\",\"volume\":\"13 1\",\"pages\":\"1137-1149\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Nonlinear Analysis and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22075/IJNAA.2022.5657\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Nonlinear Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22075/IJNAA.2022.5657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
Generalized modified ratio-cum-product kind exponentially estimator of the populations mean in stratified ranked set sample
In this study, we present a proposal aimed at estimating the finite population's mean of the main variable by stratification rank set sample (S_{t}text{RSS}) through the modification made to generalized ratio-cum-product type exponential estimator. The relative bias (text{PRB}), Mean Squared Error (text{Mse}) and percentage relative efficiencies (text{PRE}) of the proposed modified estimator is obtained to the first degree of approximation. Conditions under which the proposed estimator is more efficient than the usual unbiased estimator, ratio, product type estimators, and some other estimators are obtained. Finally, the estimators' abilities are evaluated through the use of simulations, as showed that the proposed modified estimator is more efficient as compared to several other estimators.