Estimation in two sample randomly truncated scale model

This paper studies a class of Cramér-von Mises type minimum distance estimators of the scale parameter in the two sample randomly left truncated scale models. The proposed class of estimators includes an analogue of the well-known Hodges-Lehmann estimator. The paper proves the asymptotic normality of these estimators under mild conditions. It also contains a real data application and a simulation study making a comparison of some of the estimators in the class with the ratio of the two means.