Asymptotic expansion of S-estimators of location and covariance

H. P. Lopuha

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Asymptotic expansion of S-estimators of location and covariance

机译：位置和协方差的S估计的渐近展开

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摘要

By means of a straightforward application of empirical process theory, we show that S-estimators of multivariate location and covariance are asymptotically equivalent to a sum of independent vector and matrix valued random elements respectively. This provides an alternative proof of asymptotic normality of S-estimators and clearly explains the limiting covariance structure. It also leads to a relatively simple proof of asymptotic normality of the length of the shortest -fraction.

机译：通过经验过程理论的直接应用，我们表明多元位置和协方差的S估计量渐近等效于独立矢量和矩阵值随机元素的总和。这为S估计的渐近正态性提供了另一种证明，并清楚地解释了极限协方差结构。这也导致最短分数长度的渐近正态性的相对简单证明。

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来源
《Statistica neerlandica》 |1997年第2期|220-237|共18页
作者
H. P. Lopuha;
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作者单位

Department of Mathematics and Computing Science Delft University of Technology Mekelweg 4 2628 CD Delft The Netherlands;

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正文语种 eng
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关键词
robust estimation of multivariate location and covariance; asymptotic normality of S-estimators; application of empirical process theory;

机译：多元位置和协方差的鲁棒估计;S估计的渐近正态性;经验过程理论的应用;

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7. Asymptotic expansion of S-estimators of location and covariance [O] . H. P. Lopuhaa 1997

机译：位置和协方差的S估计的渐近展开
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机译：位置和协方差s估计的渐近展开式

Asymptotic expansion of S-estimators of location and covariance

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