Regression estimator for adaptive cluster sample

Abstract

Background/Objectives: Adaptive cluster sampling (ACS) is known as a sampling design for rare and clustered objects. We suggest the regression estimator to improve the efficiency of ACS estimator. Methods/Statistical analysis: We estimate the population total of Pedicularisishidoyana Koidz. &Ohwi in the Gyeongju National Park by using the regression estimation for adaptive cluster sampling. We can consider an auxiliary variable which has strong correlation in the estimation procedure. To do this we simulate auxiliary variable has sample correlation r=0.86. The efficiency of the proposed estimator is evaluated by comparing the relative efficiency and 95% confidence limit of estimator with the typical adaptive cluster estimator.