6533b85efe1ef96bd12bf421
RESEARCH PRODUCT
Space-Time FPCA Clustering of Multidimensional Curves.
Francesca Di SalvoGiada AdelfioMarcello Chiodisubject
Dependency (UML)Computer sciencebusiness.industryClustering of multidimensional curves GAM Spatio-temporal patternSpace timeGeneralized additive modelPattern recognition010502 geochemistry & geophysics01 natural sciences010104 statistics & probabilityPrincipal component analysisArtificial intelligence0101 mathematicsCluster analysisbusinessFocus (optics)Settore SECS-S/01 - StatisticaRotation (mathematics)Smoothing0105 earth and related environmental sciencesdescription
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-01 |