An improved estimator of the finite population mean in simple random sampling

Grover, Lovleen Kumar; Kaur, Paramdeep

doi:10.3233/mas-2011-0163

Cited by 38 publications

(40 citation statements)

References 24 publications

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“…To improve the efficiency of the estimators several authors have suggested combining ratio estimator with difference estimator in different ways. Some important references are Ray and Singh (1981), Singh et al (2008), Gupta and Shabbir (2008), Grover andKaur (2011) andSolanki (2012). Motivated by these authors we suggest some improved estimators combining ratio estimator with difference estimator as:…”

Section: Proposed Estimatorsmentioning

confidence: 99%

Some calibration estimators for finite population mean in two-stage stratified random sampling

Singh

Sisodia

Nidhi³

et al. 2019

Communications in Statistics - Theory and Methods

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Some improved estimators are proposed for estimating the population mean in stratified sampling in the presence of auxiliary information. Mean square error (MSE) of the proposed estimators have been derived under large sample approximation. It has been shown that under optimum conditions proposed estimators are better than usual unbiased estimator and Hansen et al. (1946) estimator. Both theoretical and empirical findings are encouraging and support the soundness of the proposed procedure for mean estimation.

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Section: Proposed Estimatorsmentioning

confidence: 99%

Some calibration estimators for finite population mean in two-stage stratified random sampling

Singh

Sisodia

Nidhi³

et al. 2019

Communications in Statistics - Theory and Methods

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“…-Recently, Shabbir and Gupta [11] used the linear combination of two auxiliary variables to propose a di erence cum exponential ratio-type estimator. This concept was initiated by Gupta and Shabbir [24] and Grover and Kaur [31]. y SG = q 6 y+q 7 X x +q 8 Z z exp X x X + x ; (19) where q 6 , q 7 , and q 8 are the feasible constants de ned in Box V.…”

Section: Review Of Literaturementioning

confidence: 99%

Hartley-Ross Type Unbiased Estimators of Population Mean Using Two Auxiliary Variables

2018

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In survey sampling, it is a well-established phenomenon that the e ciency of estimators increases with proper information on auxiliary variable(s). Keeping this fact in mind, the information on two auxiliary variables was utilized to propose a family of Hartley-Ross type unbiased estimators for estimating population mean under simple random sampling without replacement. Minimum variance of the new estimators was derived up to the rst degree of approximation. Three real datasets were used to verify the e cient performance of the new family in comparison to the usual unbiased, Hartley and Ross, and other competing estimators.

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“…Recent works have built on both the modifications of the classical ratio or regression and the exponential ratio estimators to obtain improved efficiencies in simple random sampling. These works include [24], [10], [58], [31], [35], [35], [42], [6], [7], [8]. These works showed some improvements over the Regression estimator.…”

Section: Introductionmentioning

confidence: 99%

On the Optimal Search for Efficient Estimators of Population Mean in Simple Random Sampling in the presence of an Auxiliary Variable

Enang¹,

Ekpenyong²

2016

HJMS

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This study proposes some ratio estimators of the population mean under simple random sampling schemes, in order to tackle the problem of low efficiencies of some existing estimators. An improved exponential ratio estimator of the population mean under simple random sampling scheme and its bias and mean square error have been derived. Further propositions of a generalized form of the exponential ratio estimator of the population mean under simple random sampling scheme has also been made. The Bias and Mean Square Errors of these class of estimators have also been obtained. It is observed that some existing estimators are members of this class of estimators of population mean. Analytical and numerical results indicate that, the Asymptotic Optimal Estimator (AOE) of these proposed estimators of population mean using single auxiliary variable have been found to exhibit greater gains in efficiencies than the classical regression estimators and other existing estimators in simple random sampling scheme.

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An improved estimator of the finite population mean in simple random sampling

Cited by 38 publications

References 24 publications

Some calibration estimators for finite population mean in two-stage stratified random sampling

Some calibration estimators for finite population mean in two-stage stratified random sampling

Hartley-Ross Type Unbiased Estimators of Population Mean Using Two Auxiliary Variables

On the Optimal Search for Efficient Estimators of Population Mean in Simple Random Sampling in the presence of an Auxiliary Variable

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