Maximal autocorrelation functions in functional data analysis
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- Hooker, G. & Roberts, S. Stat Comput (2016) 26: 945. doi:10.1007/s11222-015-9582-5
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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.