Robust functional estimation using the median and spherical principal components

被引：84

作者：

Gervini, Daniel ^{[1
]}

机构：

[1] Univ Wisconsin, Dept Math Sci, Milwaukee, WI 53201 USA

来源：

BIOMETRIKA | 2008年 / 95卷 / 03期

基金：

美国国家科学基金会;

关键词：

breakdown point; influence function; nonparametric regression; outlier detection; stochastic process;

D O I：

10.1093/biomet/asn031

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We present robust estimators for the mean and the principal components of a stochastic process in L(2)(R). Robustness and asymptotic properties of the estimators are studied theoretically, by simulation and by example. It is shown that the proposed estimators are generally more robust to outliers than the commonly used sample mean and principal components, although their properties depend on the spacings of the eigenvalues of the covariance function.

引用

页码：587 / 600

页数：14

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