摘要
主成分分析方法是在经济管理中经常使用的多元统计分析方法,在变量降维方面扮演着很重要的角色,是进行多变量综合评价的有力工具。但传统的主成分分析对于异常值十分敏感,计算结果很容易受到异常值影响,而实际数据常包含异常情况,通常分析很少考虑它们的作用。本文基于MCD估计提出一种稳健的主成分分析方法,模拟和实证分析结果表明,该方法对于抵抗异常值有很好的效果。
Principal component analysis（PCA）is a frequently used muhivariable analysis method in economics and management, it plays an important role in dimension reduction and is a powerful tool for overall evaluation. But traditional PCA is very sensitive to outliers and the results are easily affected by them. Real-life data always include abnormal situations which is usually lack of consideration. A robust PCA based on MCD estmator is put forward in this paper. Simulations and empirical study prove that it is very effective in resistance of outliers.
出处
《数理统计与管理》
CSSCI
北大核心
2006年第4期462-468,共7页
Journal of Applied Statistics and Management
基金
广东省科技计划攻关项目(编号:2004B10101010)
关键词
异常值
MCD估计
主成分分析
稳健主成分分析
outliers
MCD estimator
principal component analysis
robust principal component analysis
