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Maximal autocorrelation functions in functional data analysis
Authors:Giles Hooker  Steven Roberts
Institution:1.Department of Biological Statistics and Computational Biology,Cornell University,Ithaca,USA;2.Research School of Finance, Actuarial Studies and Applied Statistics,Australian National University,Canberra,Australia
Abstract: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.
Keywords:
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