Robust methods for multivariate analysis - A tutorial review

被引：92
|
作者：
Liang, YZ
Kvalheim, OM
机构：
[1] UNIV BERGEN,DEPT CHEM,N-5007 BERGEN,NORWAY
[2] HUNAN UNIV,DEPT CHEM & CHEM ENGN,CHANGSHA,PEOPLES R CHINA
来源：
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1996年 / 32卷 / 01期
关键词：
calibration; classification; least squares; multivariate analysis; partial least squares; regression; outlier detection; robust analysis; robust regression;
D O I：
10.1016/0169-7439(95)00006-2
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Robust methods developed in statistics and chemometrics for multivariate calibration and exploratory analysis are reviewed. Robust methods can be classified according to aim: (i) regression methods, (ii) methods for outlier detection (diagnostics), and (iii) methods for dimensionality reduction (exploratory analysis). Based on this taxonomy, some of the methods are described in detail and illustrated with examples.
引用
收藏
页码：1 / 10
页数：10
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