论文标题
减少偏置的估计中位数平均绝对偏差的估计
Bias-reduced estimation of mean absolute deviation around the median
论文作者
论文摘要
为中位回归模型的平均绝对偏差参数提出了偏差降低的估计器。从常规降低偏见的估计中，通常要求缺乏平滑度，因此设计了解决方法。局部渐近正常性和巴哈杜尔 - 凯夫（Kiefer）的代表性足以证明偏见校正的有效性。该提案是在经典的渐近状态下开发的，但基于模拟，它似乎在高维度中也起作用。
A bias-reduced estimator is proposed for the mean absolute deviation parameter of a median regression model. A workaround is devised for the lack of smoothness in the sense conventionally required in general bias-reduced estimation. A local asymptotic normality property and a Bahadur--Kiefer representation suffice in proving the validity of the bias correction. The proposal is developed under a classical asymptotic regime but, based on simulations, it seems to work also in high-dimensional settings.
