TY  - JOUR
T1  - Robust regression type estimators for body mass index under extreme ranked set and quartile ranked set sampling
AU  - Çetin, Arzu Ece
AU  - Koyuncu, Nursel
PY  - 2024
DA  - June
Y2  - 2023
DO  - 10.31801/cfsuasmas.1373759
JF  - Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics
JO  - Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat.
PB  - Ankara University
WT  - DergiPark
SN  - 1303-5991
SP  - 336
EP  - 348
VL  - 73
IS  - 2
LA  - en
AB  - Robust regression-type estimators of population mean that use auxiliary variable information are proposed by considering robust methods under extreme ranked set sampling (ERSS) and quartile ranked set sampling (QRSS). We have used the data concerning body mass index (BMI) for 800 people in Turkey in 2014. The real data example is applied to see efficiency of the estimators in ERSS and QRSS designs and it is found that the proposed estimators are better in these designs than the classical ranked set sampling (RSS) design. In addition, mean square error (MSE) and percent relative efficiency (PRE) are used to compare the performance of the adapted and proposed estimators.
KW  - Robust regression estimators
KW  - extreme ranked set sampling
KW  - quartile ranked set sampling
KW  - percentage relative efficiency (PRE)
CR  - Ali, N., Ahmad, I., Hanif, M., Shahzad, U., Robust-regression-type estimators for improving mean estimation of sensitive variables by using auxiliary information, Communications in Statistics-Theory and Methods, 3 (2019), 385–390. https://doi.org/10.1080/03610926.2019.1645857
CR  - Bouza, C. N., Ranked set sampling for the product estimator, Rev. Invest. Oper, 29(3) (2008), 201–206.
CR  - Koyuncu, N., Regression estimators in ranked set, median ranked set and neoteric ranked set sampling, Pakistan Journal of Statistics and Operation Research, 14(1) (2018), 89–94. https://doi.org/10.18187/pjsor.v14i1.1825
CR  - Koyuncu, N., Al-Omari, A. I., Generalized robust-regression-type estimators under different ranked set sampling, Mathematical Sciences, (2020). https://doi.org/10.1007/s40096-020-00360-7
CR  - Long, C., Chen, W., Yang, R., Yao D., Ratio estimation of the population mean using auxiliary under the optimal sampling design, Probability in the Engineering and Informational Sciences, 3 (2022), 449–460. https://doi.org/10.1017/s0269964820000625
CR  - Mclntyre, G. A., A method for unbiased selective sampling, using ranked sets, Australian Journal of Agricultural Research, 3 (1952), 385–390. https://doi.org/10.1071/ar9520385
CR  - Mehta, N., Mandowara, V. A., A modified ratio-cum-product estimator of finite population mean using ranked set sampling, Communication in Statistics- Theory and Methods, 45(2) (2016), 267–276. https://doi.org/10.1080/03610926.2013.830748
CR  - Muttlak, H. A., Investigating the use of quartile ranked set samples for estimating the population mean, Applied Mathematics and Computation, 146 (2003), 437–443. https://doi.org/10.1016/s0096-3003(02)00595-7
CR  - Samawi, H. M., Muttlak, H. A., Estimation of ratio using rank set sampling, Biometrical Journal, 38 (1996), 753-764. https://doi.org/10.1002/bimj.4710380616
CR  - Samawi, H. M., Ahmed, M. S.,Abu-Dayyeh, W., Estimating the population mean using extreme ranked set sampling, Biometrical Journal, 38(5) (1996), 577–586. https://doi.org/10.1002/bimj.4710380506
CR  - Shahzad, U., Hanif, M., Koyuncu, N., Luengo, A. V. G., A regression type estimator for mean estimation under ranked set sampling alongside the sensitivity issue, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 68(2) (2019), 2037–2049. https://doi.org/10.31801/cfsuasmas.586057
CR  - Shahzad, U., Al-Noor, N., H., Hanif, M., Sajjad, I., Muhammad, A. M., Imputation based mean estimators in case of missing data utilizing robust regression and variance–covariance matrices, Communications in Statistics-Simulation and Computation, (2020), 1–20. https://doi.org/10.1080/03610918.2020.1740266
CR  - Subzar, M., Bouza, C. N., Al-Omari, A. I., Utilization of different robust regression techniques for estimation of finite population mean in srswor in case of presence of outliers through ratio method of estimation, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 40(5) (2019), 600–609. https://doi.org/10.32604/cmc.2020.010230
CR  - Zaman, T., Bulut, H., Modified ratio estimators using robust regression methods, Communications in Statistics-Theory and Methods, 48(8) (2019), 2019–2048. https://doi.org/10.1080/03610926.2018.1441419
UR  - https://doi.org/10.31801/cfsuasmas.1373759
L1  - https://dergipark.org.tr/en/download/article-file/3465082
ER  -