Classes of Estimators under New Calibration Schemes using Non-conventional Measures of Dispersion

Abstract

In this paper, we proposed two classes of estimators under two new calibration schemes for a heterogeneous population by incorporating auxiliary information of Non-Conventional Measures of dispersion which are robust against the presence of outlier in the data.Theoretical results are supported by simulation studies conducted on six bivariate populations generated using exponential and normal distributions. The biases and percentage relative efficiencies (PRE) of the proposed and other related estimators in the study were computed and results indicated that the estimators proposed under suggested calibration schemes perform on average more efficiently than conventional unbiased estimator, Rao and Khan (2016) and Nidhi et al. (2017). © 2021, Philippine Statistical Association, Inc.. All rights reserved.