Abstract
Clusterwise regression is applied to functional data, using PCR and PLS as regularization methods for the functional linear regression model. We compare these two approaches on simulated data as well as on stock-exchange data.
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Preda, C., Saporta, G. (2007). PCR and PLS for Clusterwise Regression on Functional Data. In: Brito, P., Cucumel, G., Bertrand, P., de Carvalho, F. (eds) Selected Contributions in Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73560-1_56
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DOI: https://doi.org/10.1007/978-3-540-73560-1_56
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