Calibration under measurement errors

Vishwakarma, Gajendra K.; Singh, Abhishek; Singh, Narendra

doi:10.1016/j.jksus.2020.07.017

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…And also, in testing or making of pernicious elements cannot be evaded, because “a miss is as good as a mile.” There are many authors for the explanation of measurement errors like Fuller (2009) 21 has discussed on liner modeling in both linear and nonlinear, to study the measurement errors, 22 have given modeling approach, ratio estimation by Shalabh 23 ; Manisha and Singh 24 ; Manisha and Singh 25 ; Gregoire and Salas 26 ; and Singh and Kumar et al 27 have illustrated measurement errors for the estimation of population parameters. Estimation through ratio and product method under correlated measurement errors has given by Shalabh and Tsai 28 and Vishwakarma et al 29 have given calibration under measurement errors.…”

Section: Introductionmentioning

confidence: 99%

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

Vishwakarma

Singh

2022

Concurrency and Computation

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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.

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