Generalized Difference-Cum Exponential Class of Estimators for Estimating Population Parameters of the Sensitive Variable
We propose a generalized class of estimators to estimate general population parameters of susceptible research variables using additional auxiliary information in SRSWOR. The population constants such as the coefficient of variation, the population mean, the standard deviation, and the population me...
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Veröffentlicht in: | Mathematical problems in engineering 2022-05, Vol.2022, p.1-11 |
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creator | Vishwakarma, Gajendra K. Yadav, Subhash Kumar Bari, Tarushree |
description | We propose a generalized class of estimators to estimate general population parameters of susceptible research variables using additional auxiliary information in SRSWOR. The population constants such as the coefficient of variation, the population mean, the standard deviation, and the population mean square are defined using a conventional estimator. The expression for the mean square errors of the proposed class is derived up to the first order of approximation. To compare the effectiveness of the proposed class of estimators, an empirical study is conducted utilizing real and simulated data sets. Theoretical and empirical research demonstrates that the suggested generalized class of estimators outperforms other current estimators. |
doi_str_mv | 10.1155/2022/7890489 |
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subjects | Abortion Coefficient of variation Engineering Estimators Parameter sensitivity Population Population statistics Variables |
title | Generalized Difference-Cum Exponential Class of Estimators for Estimating Population Parameters of the Sensitive Variable |
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