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

Auxiliary information is mostly used together with study variable to enhanceefficiency of estimators for population mean, total and variance. thompsonintroduced adaptive cluster sampling as an appropriate sampling scheme forrare and clustered populations. in present article, difference-type anddifference-cum-exponential-ratio-type estimators are presented utilizing twoauxiliary variables for estimation of general parameter under stratifiedadaptive cluster sampling. proposed estimators utilize auxiliary informationin terms of ranks, variances and means of auxiliary variables in $h^{th}$stratum. expressions for bias and mean square error of proposed estimatorsare derived using first order of approximation. numerical study is conductedto evaluate the performance of proposed estimators.