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.

本文提出了一些折衷的指数比率类型插补方法，并在缺少一些样本观测值的情况下，在简单随机抽样中提出了它们对应的点估计量。推导了拟议的点估计量的偏差和均方误差的表达式。将这些估计量与均值插补方法，比率插补（Lee等人在J Off Stat 10：231–243，1994）方法，回归插补方法，折衷插补（Singh and Horn in Metrika 51：267–276，2000）中进行比较方法，Singh和Deo（Stat Pap 44：555–579，2003）估计量，Singh（Statistics 43：499–511，2009）估计量，Gira（Appl Math Sci 9（34）：1663–1672，2015）估计量，Singh等。（Hacet J Math Stat 45（6）：1865–1880，2016年）估计量和适应指数比类型（Bahl和Tuteja in J Inform Optim Sci 12（1）：159–164，1991）估计量。已经进行了仿真研究，并且所提出的估计器比某些可比较的估计器要好。