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Tail Behavior and Breakdown Properties of Equivariant Estimators of Location

机译:等位估计器的尾部行为和分解特性

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For translation and scale equivariant estimators of location, inequalities connecting tail behavior and the finite-sample breakdown point are proved, analogous to those established by He et al. (1990, Econometrika, 58, 1195–1214) for monotone and translation equivariant estimators. Some other inequalities are given as well, enabling to establish refined bounds and in some cases exact values for the tail behavior under heavy- and light-tailed distributions. The inequalities cover translation and scale equivariant estimators in great generality, and they involve new breakdown-related quantities, whose relations to the breakdown point are discussed. The worth of tail-behavior considerations in robustness theory is demonstrated on examples, showing the impact of the basic two techniques in robust estimation: trimming and averaging. The mathematical language employs notions from regular variation theory.
机译:对于位置的平移和尺度等变估计,证明了连接尾部行为和有限样本分解点的不等式,类似于He等人建立的不等式。 (1990,Econometrika,58,1195-1214),用于单调和平移等变估计量。还给出了其他一些不等式,从而可以建立精确的边界,并且在某些情况下,可以确定在重尾分布和轻尾分布下的尾部行为精确值。不等式在很大程度上笼统地涵盖了平移和规模等变估计量,它们涉及与分解相关的新量,并讨论了其与分解点的关系。实例演示了鲁棒性理论中尾部行为考虑的价值,显示了鲁棒估计中两种基本技术的影响:修整和平均。数学语言采用了规则变化理论的概念。

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