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Uniform asymptotics for S- and MM-regression estimators

机译:S和MM回归估计量的一致渐近性

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In this paper we find verifiable regularity conditions to ensure that S-estimators of scale and regression and MM-estimators of regression are uniformly consistent and uniformly asymptotically normally distributed over contamination neighbourhoods. Moreover, we show how to calculate the size of these neighbourhoods. In particular, we find that, for MM-estimators computed with Tukey's family of bisquare score functions, there is a trade-off between the size of these neighbourhoods and both the breakdown point of the S-estimators and the leverage of the contamination that is allowed in the neighbourhood. These results extend previous work of Salibian-Barrera and Zamar for location-scale to the linear regression model.
机译:在本文中,我们找到可验证的正则条件,以确保规模和回归的S估计量和回归的MM估计量在污染邻域内一致一致且渐近正态分布。此外,我们展示了如何计算这些社区的规模。特别是,我们发现,对于使用Tukey的双平方得分函数族计算的MM估计量,这些邻域的大小与S估计量的分解点以及污染的杠杆之间存在一个权衡允许在街区。这些结果将Salibian-Barrera和Zamar先前关于位置尺度的工作扩展到了线性回归模型。

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