Estimation of General Parameter Under Stratified Adaptive Cluster Sampling Based on Dual Use of Auxiliary Information

Abstract

Auxiliary information is mostly used together with study variable to enhance efficiency of estimators for population mean, total and variance. Thompson introduced adaptive cluster sampling as an appropriate sampling scheme for rare and clustered populations. In present article, difference-type and difference-cum-exponential-ratio-type estimators are presented utilizing two auxiliary variables for estimation of general parameter under stratified adaptive cluster sampling. Proposed estimators utilize auxiliary information in terms of ranks, variances and means of auxiliary variables in $h^{th}$ stratum. Expressions for bias and mean square error of proposed estimators are derived using first order of approximation. Numerical study is conducted to evaluate the performance of proposed estimators.