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.
- Version0.1.3
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release01/06/2023
Team
Marc Vidal
Ana Mª Aguilera
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