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Robust principal component analysis for functional data. (With comments). (English) Zbl 0980.62049

Summary: A method for exploring the structure of populations of complex objects, such as images, is considered. The objects are summarized by feature vectors. The statistical backbone is Principal Components Analysis in the space of feature vectors. Visual insights come from representing the results in the original data space. In an ophthalmological example, endemic outliers motivate the development of a bounded influence approach to PCA.

MSC:

62H25 Factor analysis and principal components; correspondence analysis
62H99 Multivariate analysis
62A09 Graphical methods in statistics

Software:

fda (R)
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References:

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