论文标题
修剪残差估计量最小平方的渐近正态性
Asymptotic normality of the least sum of squares of trimmed residuals estimator
论文作者
论文摘要
为了增强残差估计量的经典最小平方（LS）的鲁棒性，Zuo（2022）引入了修剪（LST）残差估计器的最小平方。 LST享有许多期望的特性，并且可以作为LS的强大替代品。它的渐近特性，包括强和根-N的一致性，而渐近正态性则未得到解决。本文解决了这一问题。
To enhance the robustness of the classic least sum of squares (LS) of the residuals estimator, Zuo (2022) introduced the least sum of squares of trimmed (LST) residuals estimator. The LST enjoys many desired properties and serves well as a robust alternative to the LS. Its asymptotic properties, including strong and root-n consistency, have been established whereas the asymptotic normality is left unaddressed. This article solves this remained problem.
