文件名称:a-MATLAB-library-for-robust
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介绍一个稳健性分析工具箱。主要做稳健性主成分、主成分回归、分类。-Our toolbox currently contains implementations of robust
methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-LTS, MCD-regression), principal
component analysis (RAPCA, ROBPCA), principal component regression (RPCR), partial least squares (RSIMPLS) and classification
(RDA). Only a few of these methods will be highlighted in this paper. The toolbox also provides many graphical tools to detect and classify
the outliers. The use of these features will be explained and demonstrated through the analysis of some real data sets.
methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-LTS, MCD-regression), principal
component analysis (RAPCA, ROBPCA), principal component regression (RPCR), partial least squares (RSIMPLS) and classification
(RDA). Only a few of these methods will be highlighted in this paper. The toolbox also provides many graphical tools to detect and classify
the outliers. The use of these features will be explained and demonstrated through the analysis of some real data sets.
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a MATLAB library for robust.pdf