In the literature, auxiliary information is used by authors to construct various efficient estimators of different population parameters. This chapter discusses a difference-cum-exponential type estimator and studied their properties,...
moreIn the literature, auxiliary information is used by authors to construct various efficient estimators of different population parameters. This chapter discusses a difference-cum-exponential type estimator and studied their properties, motivated by T. J. Rao, E. J. Ekpenyong and E. I. Enang. It aims to derive the expression for the bias and mean squared error and gives the conditions for minimum mean square error. The chapter considers some real-life populations to show the efficiency of the proposed estimator over existing estimators. It examines the performance of the proposed estimator by considering seven different real-life populations and also by a simulation study. Further, to get a better result, researchers worked on difference and exponential type estimators and showed its usefulness. The ratio estimator works better when there is a positive correlation between study and auxiliary variables, while the product estimator performs well in case of the negative correlation.
