Sharif University of Technology Scientia Iranica 1026-3098 29 4 2022 08 01 Generalized Variance Estimator using Auxiliary Information in the Presence and Absence of Measurement Error 1868 1879 22751 10.24200/sci.2022.57298.5164 EN M. Umair Tariq Department of Statistics, National College of Business, Administration and Economics, Lahore, Pakistan 0000-0002-4071-4548 M. Nouman Qureshi Department of Statistics, National College of Business, Administration and Economics, Lahore, Pakistan 0000-0002-6006-3308 M. Hanif Department of Statistics, National College of Business, Administration and Economics, Lahore, Pakistan 0000-0002-0775-3457 Journal Article 2020 12 14 In this study, we have proposed a new generalized estimator using auxiliary information for the estimation of population variance in presence and absence of measurement error. The expressions approximate bias and mean square error of the proposed generalized estimator are derive up to the first-order. Several new and existing estimators are found as the special cases of proposed estimator and expressed on various values of optimizing and generalized constants. The proposed estimator is compared mathematically with some existing estimators under certain conditions. The performance of proposed estimator is observed by simulation and real data application under different sample sizes. It is observed that the proposed estimator performed well than other competing estimators in the presence and absence of measurement error. https://scientiairanica.sharif.edu/article_22751_27ec7e21a73071c6aa10d3aac5cfb96e.pdf