Ratio estimators of the population mean with missing values using ranked set sampling

Al-Omari, Amer Ibrahim; Bouza, Carlos N.

doi:10.1002/env.2286

Cited by 30 publications

(19 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For k = 6, we have to select 36 units from the population and then measure only 6 units of them to be a neoteric ranked set sample which are Y [4] , Y [9] , Y [16] , Y [21] , Y [28] , Y [33] .The NRSS mean estimator can be obtained as…”

Section: Uniform Distributionmentioning

confidence: 99%

“…[4] , Y [9] ) + Cov ( Y [4] , Y [16] ) + Cov ( Y [4] , Y [21] ) + Cov ( Y [4] , Y [28] ) + Cov ( Y [4] , Y [33] ) + Cov ( Y [9] , Y [16] ) + Cov ( Y [9] , Y [21] ) + Cov ( Y [9] , Y [28] ) + Cov ( Y [9] , Y [33] ) + Cov ( Y [16] , Y [21] ) …”

Section: Uniform Distributionunclassified

“…Bouza [7] and Al-Omari and Bouza [4] considered the problem of estimation of population mean in the RSS with missing values. Al-Saleh and Al-Omari [5], Al-Omari and Al-Saleh [3] and Al-Omari [1], [2] proposed some mean estimators in other variations of the RSS.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

New ranked set sampling for estimating the population mean and variance

Zamanzade¹

2015

HJMS

View full text Add to dashboard Cite

The purpose of this study is to suggest a new modification of the usual ranked set sampling (RSS) method, namely; neoteric ranked set sampling (NRSS) for estimating the population mean and variance. The performance of the empirical mean and variance estimators based on NRSS are compared with their counterparts in ranked set sampling and simple random sampling (SRS) via Monte Carlo simulation. Simulation results revealed that the NRSS estimators perform much better than their counterparts using RSS and SRS designs when the ranking is perfect. When the ranking is imperfect, the NRSS estimators are still superior to their counterparts in ranked set sampling and simple random sampling methods. These findings show that the NRSS provides a uniform improvement over RSS without any additional costs. Finally, an illustrative example of a real data is provided to show the application of the new method in practice.

show abstract

Section: Uniform Distributionmentioning

confidence: 99%

Section: Uniform Distributionunclassified

See 1 more Smart Citation

New ranked set sampling for estimating the population mean and variance

Zamanzade¹

2015

HJMS

View full text Add to dashboard Cite

show abstract

“…These are used in many areas of research, including economics (Knottnerus 2011), medicine (Al-Omari andBouza 2015), agriculture (Francis et al 1979;Reich et al 1993), land-use assessment (Li et al 2014) and animal ecology (Stevenson 1979;Neilson et al 2013). Their principles are described by Cochran (1977, Chap.…”

Section: Introductionmentioning

confidence: 99%

“…6) and theoreticians continue to develop them for particular circumstances (e.g. Oral and Oral 2011;Lin and Chao 2014;Magnussen et al 2014;Al-Omari and Bouza 2015;Weiskittel et al 2015;Kumar and Chhaparwal1 2016;Ringvall et al 2016). Another method that is being used increasingly is 'model-assisted' estimation; Baffetta et al (2009) offer a formal and generalised description of its approach whilst Kangas et al (2016) offer a recent example of its use.…”

Section: Introductionmentioning

confidence: 99%

Simulation studies to examine bias and precision of some estimators that use auxiliary information in design-based sampling in forest inventory

West

2017

N.Z. j. of For. Sci.

View full text Add to dashboard Cite

Background: Various double sampling methods using both target and auxiliary variables have been developed over many years for use in natural resource inventory. Methods: Simulations of inventory were carried out using four different ratio estimators and model-assisted estimation in each of five rather different example forest populations. Estimates of population means and their standard errors from each of these methods were compared with those obtained using simple random sampling. Results: With all five double sampling estimators, bias in estimates of means and standard errors (the latter estimated analytically or through bootstrapping) was generally small and consistent with theoretical expectations. Their efficiency increased as either the first-or second-phase sample sizes increased. All were more efficient than estimates obtained using simple random sampling as long as there was some positive level of correlation between the target and auxiliary variable. However, none of the double sampling estimators was more efficient than any of the others. Conclusions: For many forest inventory tasks, users may well be able to use whichever of the estimators is most convenient to their purpose. However, model-assisted estimation has application in a wider range of circumstances than the other methods, which perhaps recommends it for general use.

show abstract

Computing the effect of measurement errors on ranked set sampling estimators of the population mean

Vishwakarma

Singh

2022

Concurrency and Computation

View full text Add to dashboard Cite

Summary The effect of measurement errors shows the seriousness of the estimators or the estimation procedures and cannot be avoided in sensitive cases because “a miss is as good as a mile.” In this article, we have proposed the very first ranked set estimators like unbiased, ratio, product, difference, ratio exponential, and product exponential estimators under both correlated and uncorrelated measurement errors. The expressions for bias and mean square error of the proposed estimators are obtained up to the first order of approximation. The proposed ranked set estimators have been compared through relative efficiencies over unbiased estimators and the effect of measurement errors has been given through percentage computation of measurement errors. The theoretical conditions are obtained under which the proposed estimator has performed better. The performance of the proposed ranked set estimators under measurement errors are shown by efficiency comparisons, Monte‐Carlo simulation study, and real data study.

show abstract

Ratio estimators of the population mean with missing values using ranked set sampling

Cited by 30 publications

References 26 publications

New ranked set sampling for estimating the population mean and variance

New ranked set sampling for estimating the population mean and variance

Simulation studies to examine bias and precision of some estimators that use auxiliary information in design-based sampling in forest inventory

Computing the effect of measurement errors on ranked set sampling estimators of the population mean

Contact Info

Product

Resources

About