Citation

Sinha RR, Khanna B. Concurr. Comput. 2022; 34(18): e7023.

Copyright

(Copyright © 2022, John Wiley and Sons)

DOI

10.1002/cpe.7023

PMID

unavailable

Abstract

This research paper deals with the problem of estimating population mean of study variable using information of auxiliary variable under varying probability and measurement error. Motivated by Kadilar and Cingi, App Math Lett, 2006, 19, 75 and Zaman, Stat Trans-New Ser, 2020, 21, 159, generalized ratio and product enhanced regressed exponential (ERE) estimators are proposed to estimate the population mean using different auxiliary parameters under the sampling of probability proportional to size (pps) and extended for the case of measurement error. Further, following the strategies of Naik and Gupta, J Ind Soc Agr Stat, 1996, 48, 151; Jhajj et al., Pak J Stat, 2006, 23, 1; Singh et al., Auxiliary Information and A Priori Values in Construction of Improved Estimators, Renaissance High Press, 2007; and Solanki and Singh, Chil J Stat, 2013, 4, 3, conventional ratio, product, regression, generalized and many other types of estimators have been adopted under pps sampling with and without measurement error. Up to the first order of large sample approximation, the bias and mean square error (MSE) of the suggested ERE and adopted estimators are derived and their properties have been studied. Comparisons have been made theoretically and empirically to comprehend the merits of recommended estimators over the conventional and adopted estimators.

Language: en

Keywords

auxiliary; mean; measurement error; pps sampling