Generalized Chain Exponential Product in Regression Estimator for estimating the Mean in Nutritional and Agricultural Sciences (International Journal of Food and Nutritional Sciences, 2021)
The ancillary information is broadly employed in sample surveys to estimate the mean in Nutritional Science. Numerous research works for estimating the population mean using one or more than one ancillary variables have been completed. The recent research paper proposes generalized chain exponential product-in-regression estimator for population mean using the information on the ancillary and the additional ancillary variables. The bias and mean square error expressions for the generalized chain exponential product-in-regression estimator, have been derived in case of large sample approximation. An efficiency comparison of the proposed estimators has also been made. Further by using real data sets, numerical study is also given to verify the theoretical results.