$M$的新算法--多元散射和定位的估计
New Algorithms for $M$-Estimation of Multivariate Scatter and Location
摘要：
我们提出了新的算法$M$ -估计的多元分散和位置和对称化的$M$ -估计的多元分散。新算法比目前使用的定点和相关算法快得多。其主要思想是利用目标泛函的二阶泰勒展开，并设计了一个部分牛顿-拉夫森程序。与对称化的$M$ -估计，我们工作与不完全的$U$ -统计，以加快我们的程序最初。
英文摘要：
We present new algorithms for $M$-estimators of multivariate scatter and location and for symmetrized $M$-estimators of multivariate scatter. The new algorithms are considerably faster than currently used fixed-point and related algorithms. The main idea is to utilize a second order Taylor expansion of the target functional and to devise a partial Newton-Raphson procedure. In connection with symmetrized $M$-estimators we work with incomplete $U$-statistics to accelerate our procedures initially.
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