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Improved population mean estimator with exponential function under non-response
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作者 CerenUnal Cem Kadilar 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2023年第4期562-580,共19页
In this article,we consider a new family of exponential type estimators for estimating the unknown population mean of the study variable.We propose estimators taking advantage of the auxiliary variable information und... In this article,we consider a new family of exponential type estimators for estimating the unknown population mean of the study variable.We propose estimators taking advantage of the auxiliary variable information under the first and second non-response cases separately.The required theoretical comparisons are obtained and the numerical studies are conducted.In conclusion,the results show that the proposed family of estimators is the most efficient estimator with respect to the estimators in literature under the obtained conditions for both cases. 展开更多
关键词 NON-RESPONSE exponential estimators sub-sampling method population mean
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New Class of Almost Unbiased Modified Ratio Cum Product Estimators with Knownparameters of Auxiliary Variables
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作者 Jambulingam Subramani Master Ajith S 《Journal of Mathematics and System Science》 2017年第9期248-260,共13页
This manuscript deals with new class of almost unbiased ratio cum product estimators for the estimation of population mean of the study variable by using the known values auxiliary variable. The bias and mean squared ... This manuscript deals with new class of almost unbiased ratio cum product estimators for the estimation of population mean of the study variable by using the known values auxiliary variable. The bias and mean squared error of proposed estimators are obtained. An empirical study is carried out to assess the efficiency of proposed estimators over the existing estimators with the help of some known natural populations and it shows that the proposed estimators are almost unbiased and it perform better than the existing estimators. 展开更多
关键词 Auxiliary variable BIAS mean squared error Natural populations Ratio and Productestimators Simple random sampling.
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