pfica: Independent Components Analysis Techniques for Functional Data
Performs smoothed (and non-smoothed) principal/independent components analysis
of functional data. Various functional pre-whitening approaches are implemented as
discussed in Vidal and Aguilera (2022) “Novel whitening approaches in functional
settings", <doi:10.1002/sta4.516>. Further whitening representations of functional
data can be derived in terms of a few principal components, providing an avenue
to explore hidden structures in low dimensional settings: see Vidal,
Rosso and Aguilera (2021) “Bi-smoothed functional independent component
analysis for EEG artifact removal”, <doi:10.3390/math9111243>.
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