Article ID Journal Published Year Pages File Type
10526786 Statistics & Probability Letters 2005 9 Pages PDF
Abstract
Similar to the ordinary principal component analysis (PCA), we develop PCA in L1 satisfying an invariance property: The objective function, which is a matrix norm, is transposition invariant. The new method is robust and specifically useful for long-tailed data. An example is provided.
Keywords
Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
Preview
Transposition invariant principal component analysis in L1 for long tailed data
Authors
,