Preliminary estimators of population mean using ranked set sampling in the presence of measurement error and non-response error with applications and simulation study

In order to estimate the population mean in the presence of both non-response and measurement errors that are uncorrelated, the paper presents some novel estimators employing ranked set sampling by utilizing auxiliary information. Up to the first order of approximation, the equations for the bias and mean squared error of the suggested estimators are produced, and it is found that the proposed estimators outperform the other existing estimators analysed in this study. Investigations using simulation studies and numerical examples show how well the suggested estimators perform in the presence of measurement and non-response errors. The relative efficiency of the suggested estimators compared to the existing estimators has been expressed as a percentage, and the impact of measurement errors has been expressed as a percentage computation of measurement errors.

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Publication Details

Journal
Brazilian Journal of Biometrics
Published
2024-08-30
DOI
https://doi.org/10.28951/bjb.v42i3.702
Citations
1
Primary Topic
Survey Sampling and Estimation Techniques
Type
article
Field-Weighted Citation Impact
0.71
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article

Preliminary estimators of population mean using ranked set sampling in the presence of measurement error and non-response error with applications and simulation study

Anamika Kumari, Rajesh Singh
1 citations
Brazilian Journal of Biometrics
Survey Sampling and Estimation Techniques
0.71
article

Preliminary estimators of population mean using ranked set sampling in the presence of measurement error and non-response error with applications and simulation study

Anamika Kumari, Rajesh Singh
article en
1 citations

Abstract

In order to estimate the population mean in the presence of both non-response and measurement errors that are uncorrelated, the paper presents some novel estimators employing ranked set sampling by utilizing auxiliary information. Up to the first order of approximation, the equations for the bias and mean squared error of the suggested estimators are produced, and it is found that the proposed estimators outperform the other existing estimators analysed in this study. Investigations using simulation studies and numerical examples show how well the suggested estimators perform in the presence of measurement and non-response errors. The relative efficiency of the suggested estimators compared to the existing estimators has been expressed as a percentage, and the impact of measurement errors has been expressed as a percentage computation of measurement errors.

Brazilian Journal of BiometricsVol. 42(3)
Banaras Hindu University (IN)
Openalex Percentile: Top 27%
Survey Sampling and Estimation Techniques
0.71
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Preliminary estimators of population mean using ranked set sampling in the presence of measurement error and non-response error with applications and simulation study — Anamika Kumari, Rajesh Singh · Brazilian Journal of Biometrics (2024) | TGRS Research Map | TGRS