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Maximal autocorrelation functions in functional data analysis

Hooker, Giles; Roberts, Steven


This paper proposes a new factor rotation for the context of functional principal components analysis. This rotation seeks to re-express a functional subspace in terms of directions of decreasing smoothness as represented by a generalized smoothing metric. The rotation can be implemented simply and we show on two examples that this rotation can improve the interpretability of the leading components.

CollectionsANU Research Publications
Date published: 2015
Type: Journal article
Source: Statistics and Computing
DOI: 10.1007/s11222-015-9582-5


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