Estimation of general parameters under stratified adaptive cluster sampling based on dual use of auxiliary information

Auxiliary information is used mostly in conjunction with study variables to enhance the efficiency of estimators for population mean, total, and variance. Thompson introduced adaptive cluster sampling as an appropriate sampling scheme for rare and clustered populations. This paper presents difference-type and difference-cum-exponential-ratio-type estimators utilizing two auxiliary variables for estimating general parameters under stratified adaptive cluster sampling. The proposed estimators utilize auxiliary information in terms of ranks, variances, and means of auxiliary variables in hth stratum. Expressions for bias and mean square error of the proposed estimators are derived using first-order approximation. This numerical study aims to evaluate the performance of the proposed estimators. (C) 2021 Sharif University of Technology. All rights reserved.