OUTLIER DETECTION BY ROBUST ALTERNATING REGRESSION

被引：8
|
作者：
UKKELBERG, A [1 ]
BORGEN, OS [1 ]
机构：
[1] UNIV TRONDHEIM,NORWEGIAN INST TECHNOL,DIV PHYS CHEM,N-7034 TRONDHEIM,NORWAY
来源：
ANALYTICA CHIMICA ACTA | 1993年 / 277卷 / 02期
关键词：
ALTERNATING REGRESSION; OUTLIER DETECTION;
D O I：
10.1016/0003-2670(93)80460-3
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
The sum of least-squares regression method is normally used when principal components are extracted from a data matrix. This may result in a misleading set of principal components if outliers are present in the data set, in terms of both the number of components and their direction in vector space. Therefore, a robust alternating regression method is proposed. This method can be used to detect and correct or eliminate outliers.
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页码：489 / 494
页数：6
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