Generalized difference-cum-exponential estimator in adaptive cluster sampling

In this paper,a generalized difference-cum-exponential form estimators have been proposed with two auxiliary variables in adaptive cluster sampling design. the suggested estimator is based on the networks averages intersected with the first sample selected by simple random sampling without replacement. it is observed that several estimators are special cases of proposed estimator in adaptive cluster sampling. the expressions for the mean square error and bias of the proposed estimator has been derived. the proposed class of estimators can be used for estimation of the population mean. to reveal and evaluate the efficiencies of the proposed estimator the simulation studies have been carried out. © 2017 pakistan journal of statistics.