Maximal autocorrelation functions in functional data analysis
- First Online:
- Cite this article as:
- Hooker, G. & Roberts, S. Stat Comput (2016) 26: 945. doi:10.1007/s11222-015-9582-5
- 194 Downloads
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.