Preliminary estimators of population mean using ranked set sampling in the presence of measurement error and non-response error with applications and simulation study
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Resumo
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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Referências
Bouza-Herrera C.N. : Handling missing data in ranked set sampling, Springer.(2013)
Cochran, W.G. : Sampling Techniques, third edition. New York, John Wiley and Sons.(1977)
Dell, T.R. & Clutter, J.L.: Ranked set sampling theory with order statistics background. Biometrics 28 545-555.(1972) https://doi.org/10.2307/2556166
El-Bardy, M.A. : A sampling procedure for mailed questionnaires. J. Amer. Statist. Assoc., 51, 209-227.(1956) https://doi.org/10.1080/01621459.1956.10501321
Hansen, M.H & Hurwitz W.N. : The problem of non-response in sample surveys. Journal of the American Statistical Association. 41(236), 517-529.(1946) https://doi.org/10.2307/2280572
Khalil, S., Gupta, S., & Hanif, M. : Estimation of finite population mean in stratified sampling using scrambled responses in the presence of measurement errors.Communications in Statistics-Theory and Methods 48(6), 1553-1561.(2019) https://doi.org/10.1080/03610926.2018.1435817
Khare, B.B. & Srivastava, S. : Estimation of population mean using auxiliary character in presence of non-response. Nat. Acad. Sci. Lett., 16, 111-114.(1993) http://dx.doi.org/10.12785/ijcts/060106
Kumar, M., Singh, R., Singh, A. K. and Smarandache, F. : Some ratio type estimators under measurement errors. World Applied Sci. Journal, 14(2), 72-76.(2011) http://dx.doi.org/10.6084/M9.FIGSHARE.1502622
Malik, S. and Singh, R. : An improved class of exponential ratio-type estimator in the presence of measurement errors. OCTOGON Mathematical Magazine, 21(1), 50-58.(2013)
McIntyre, G.A. : A method of unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3, 385-390.(1952) https://doi.org/10.1198/000313005X54180
Mishra, P., Adichwal, N.K. & Singh, R. : A New Log-Product-Type Estimator Using Auxiliary Information. Journal of Scientific Research, 61, 179-183.(2017)
Rehman, S.A. & Shabbir, J. : An efficient class of estimators for finite population mean in the presence of non-response under ranked set sampling (RSS). PLos ONE, 17(12).(2022) https://doi.org/10.1371/journal.pone.0277232
Shalabh, S. : Ratio method of estimation in the presence of measurement errors. J Indian Soc. Agric. Stat., 50, 150-155.(1997)
Singh, S. : Advanced Sampling Theory with Applications. Kluwer Academic Publishers.(2003)
Singh, H. P. and Karpe, N. : Ratio - product estimator for population mean in presence of measurement errors. Journal of Applied Statistical Sciences, 16, 49-64.(2008)
Singh, R., Kumar, M., Chaudhary, M.K. & Smarandache, F. : Estimation of mean in presence of non-response using exponential estimator. ArXiv, 906-2462.(2009)
Singh, R., Malik, S. & Khoshnevisan, M. : An alternative estimator for estimating the finite population mean in presence of measurement errors with the view to financial modeling. Science journal of Applied Mathematics and Statistics, 2(6), 107-111.(2014) http://dx.doi.org/10.11648/j.sjams.20140206.11
Singh, R., Mishra, P. & Khare, S. : Estimation of finite population mean under measurement error. Int. J. Comp. Theo. Stat., 6(1), 107-111.(2019) https://doi.org/10.12785/IJCTS%2F060108
Takahasi, K. & Wakimoto, K. : On unbiased estimates of the population mean based on the sample stratified using ordering. Annals of Institute of Statistical Mathematics, 20, 1-31.(1968) https://doi.org/10.1007/BF02911622
Vishwakarma, G., & Singh, A. : Computing the effect of measurement errors on ranked set sampling estimators of the population mean. Concurrency Computat. Pract. Exper., 34(27).(2022) http://dx.doi.org/10.1002/cpe.7333
Zahid, E., & Shabbir, J. : Estimation of population mean in the presence of measurement error and non-response under stratified random sampling.PLos ONE,13(2).(2018) https://doi.org/10.1371/journal.pone.0191572