In this paper, the ratio estimators are suggested which perform better than other ratio estimators in the presence of outliers using redescending M-estimator. For this purpose, we adopt the ratio estimators proposed by Kadilar and Cingi (Appl Math Comput 151:893–902, 2004) using robust regression. The proposed ratio estimators are based on redescending M-estimator proposed by Noor-ul-Amin et al. (J Reliab Stat Stud 11(2):69–80, 2018). A simulation study is conducted to compare the proposed estimators with the available estimators in the literature. Two real-life examples are presented to demonstrate the performance of proposed estimators. Furthermore, a simulation study is conducted to prove the efficiency of the proposed estimators.

在本文中，提出了比率估计器，该值估计器在存在使用离群M估计器的异常值的情况下比其他比率估计器要好。为此，我们采用鲁棒回归，采用Kadilar和Cingi（Appl Math Comput 151：893–902，2004）提出的比率估计量。提议的比率估计器基于Noor-ul-Amin等人提出的重新升序M估计器。（J Reliab Stat Stud 11（2）：69–80，2018）。进行了仿真研究，以将建议的估计量与文献中的可用估计量进行比较。给出了两个真实的例子，以证明拟议估计量的性能。此外，进行了仿真研究以证明所提出的估计器的效率。