2015
DOI: 10.15672/hjms.201510114186
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Some estimator types for population mean using linear transformation with the help of the minimum and maximum values of the auxiliary variable

Abstract: Grover et al. [4] suggested two product type exponential estimators using linear transformation of auxiliary variable. This paper proposes ratio, product and product type exponential estimators of population mean using new three linear transformations. Transformations using the known minimum and maximum values of the auxiliary variable x have been considered. Theoretically, mean square errors (MSE) and biases equations of our proposed estimators are derived up to the first order approximation. The proposed est… Show more

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Cited by 7 publications
(4 citation statements)
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“…[12] proposed a generalized family of dual to ratio-cum-product Y estimators with known auxiliary parameters. [13] developed a new ratio estimator for Y utilizing linear transformation of X as minimum and maximum values. Using auxiliary parameters, [14] provided several efficient estimators for Y .…”
Section: Estimation Under Classical Sampling Theorymentioning
confidence: 99%
“…[12] proposed a generalized family of dual to ratio-cum-product Y estimators with known auxiliary parameters. [13] developed a new ratio estimator for Y utilizing linear transformation of X as minimum and maximum values. Using auxiliary parameters, [14] provided several efficient estimators for Y .…”
Section: Estimation Under Classical Sampling Theorymentioning
confidence: 99%
“…[3] improved the estimation of the finite population mean using a stratified random sampling strategy. For more details, see [4][5][6][7] and references therein.…”
Section: Introductionmentioning
confidence: 99%
“…[18] optimized the estimate of the finite population mean under largest and smallest observations using a two-phase sampling method. For more details, see [2] , [3] , [4] , [8] , [9] , [11] , [12] , [19] , [26] and references therein.…”
Section: Introductionmentioning
confidence: 99%