2017
DOI: 10.15672/hjms.2017.442
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Abstract: Estimation of population mean is of prime concern in many studies and ratio estimators are popular choices for it. It is a common practice to use conventional measures of location to develop ratio estimators using information on auxiliary variables. In this article, we propose a class of ratio estimators for a finite population mean using information on two auxiliary variables with the help of some non-conventional location measures. We have incorporated tri-mean, Hodges-Lehmann, mid-range and decile mean of t… Show more

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Cited by 5 publications
(7 citation statements)
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References 29 publications
(40 reference statements)
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“…The MSE of these estimators is given in (16). We obtained the MSE values of proposed classical estimators in (15), the unbiased estimator, Isaki estimator in (2), Singh et al estimator in (4), the regression estimator in (7), Upadhyaya and Singh estimator in (9), and Kadilar and Cingi estimators in (11). These values are given in the uncontaminated data part of Table 4.…”
Section: Applicationsmentioning
confidence: 99%
See 1 more Smart Citation
“…The MSE of these estimators is given in (16). We obtained the MSE values of proposed classical estimators in (15), the unbiased estimator, Isaki estimator in (2), Singh et al estimator in (4), the regression estimator in (7), Upadhyaya and Singh estimator in (9), and Kadilar and Cingi estimators in (11). These values are given in the uncontaminated data part of Table 4.…”
Section: Applicationsmentioning
confidence: 99%
“…Efficient estimators for the population variance has been discussed by various authors referred to Kadilar and Cingi [1], Khan and Shabbir [2], Singh et al [3], Yadav et al [4], Yaqub and Shabbir [5], Singh and Pal [6], Sanaullah et al [7], Muneer et al [8], Housila et al [9] and Sharma et al [10]. However, in the presence of unusual observations in the data, since the classical estimators are sensitive to these extreme values, their efficiencies decrease [11]. Therefore, to reduce the negative effect of the unusual observation problem in the data, it is suggested to use the robust regression estimate, the minimum covariance determinant (MCD), and the minimum volume ellipsoid (MVE) estimators instead of the classical ones.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, these datasets are a good realization of the both with and without outlier observation cases. Moreover, these population datasets are frequently used in many studies to compare the performance of various estimators of population mean and variance, see for example, [28,29,33,48,49]…”
Section: Numerical Comparison In Presence Of Outliersmentioning
confidence: 99%
“…The ratio, product, regression, exponential and their different combinations are a popular choice, in practice, to enhance the efficiency of the estimators of population mean and variance in the presence of auxiliary information correlated with the study variable. The use of these estimators is expanding to a variety of fields such as yield estimation in agriculture, demographic studies, environmental Recently, ratio-type estimators for estimation of population mean have been developed which incorporate auxiliary information on nonconventional measures [28][29][30][31][32]. These non-conventional measures are somewhat robust and outlier resistant which aids in stabilizing the mean square error of the estimators in presence of outliers [8,33,34].…”
Section: Introductionmentioning
confidence: 99%
“…28 Nowadays the estimators based on robust techniques got popularity in the literature of survey sampling. Abid et al 29 enhanced the performance of ratio estimators using some robust measures of location and dispersion. Zaman 30 and Zaman and Bulut 31 introduced improved and modified ratio estimators based on some robust regression methods.…”
mentioning
confidence: 99%