Log Type Estimators Using Multi-Auxiliary Information Under Ranked Set Sampling

Shashi  Bhushan; Anoop  Kumar

Authors

Shashi Bhushan Department of Statistics, University of Lucknow, Lucknow, U.P., India
Anoop Kumar Department of Statistics, Central University of Haryana, Mahendergarh, India

Keywords:

Mean square error, auxiliary information, ranked set sampling

Abstract

It is well known that the relevant utilization of auxiliary information associated with the auxiliary variable helps to enhance the efficiency of the estimates. Therefore, we introduce some log
type estimators based on multi-auxiliary information under ranked set sampling. The mean square error (MSE) of the suggested estimators is derived to the first order approximation. The efficiency conditions are obtained by comparing the MSE of the suggested estimators with the MSE of the contemporary estimators. Further, numerical and simulation studies are conducted over real and artificially generated populations to support the theoretical results. The empirical results show that the suggested estimators perform better than the usual mean estimator, classical ratio estimator, AbuDayyeh et al. (2009) estimator, Mehta and Mandowara (2014) estimator, Khan and Shabbir (2016) estimator and Khan et al. (2019) estimator

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