An Exponential Class Estimator of Mean in the Presence of Correlated Measurement

Abstract

In this manuscript, an  exponential class of estimators is proposed to estimate the average of the population by using auxiliary variables in the presence of measurement error (me ) as well as correlated measurement error (cme).  The estimation for the average is done for the systematic sampling technique. The impact me and cme on the mse of the estimators is obtained in terms of mean square error (mse)  and bias. The mean  square error is also obtained for the  ratio, product and regression estimator under correlated measurement error. To  validate the results of the theoretical findings  simulation studies is done by using R programming.