Some Compromised Exponential Ratio Type Imputation Methods in Simple Random Sampling

In this paper, some compromised exponential ratio type imputation methods have been suggested and their corresponding point estimators have been proposed in simple random sampling when some sample observations are missing. The expressions for the biases and mean square errors of the proposed point estimators have been derived. These estimators are compared with the mean imputation method, ratio imputation (Lee et al in J Off Stat 10:231–243, 1994) method, regression imputation method, compromised imputation (Singh and Horn in Metrika 51:267–276, 2000) method, Singh and Deo (Stat Pap 44:555–579, 2003) estimator, Singh (Statistics 43:499–511, 2009) estimator, Gira (Appl Math Sci 9(34):1663–1672, 2015) estimator, Singh et al. (Hacet J Math Stat 45(6):1865–1880, 2016) estimators and Adapted exponential ratio type (Bahl and Tuteja in J Inform Optim Sci 12(1):159–164, 1991) estimator. Simulation studies have been performed and the proposed estimators are better than some comparable estimators.