Asymptotic theory for robust principal components
نویسندگان
چکیده
منابع مشابه
Asymptotic distributions of principal components based on robust dispersions
Algebraically, principal components can be defined as the eigenvalues and eigenvectors of a covariance or correlation matrix, but they are statistically meaningful as successive projections of the multivariate data in the direction of maximal variability. An attractive alternative in robust principal component analysis is to replace the classical variability measure, i.e. variance, by a robust ...
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This work studies the problem of sequentially recovering a sparse vector St and a vector from a low-dimensional subspace Lt from knowledge of their sum Mt := Lt + St. If the primary goal is to recover the low-dimensional subspace in which the Lt’s lie, then the problem is one of online or recursive robust principal components analysis (PCA). An example of where such a problem might arise is in ...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 1987
ISSN: 0047-259X
DOI: 10.1016/0047-259x(87)90099-6