Implementations of the k-means, hierarchical agglomerative and DBSCAN clustering methods for functional data which allows for jointly aligning and clustering curves. It supports functional data defined on one-dimensional domains but possibly evaluating in multivariate codomains. It supports functional data defined in arrays but also via the 'fd' and 'funData' classes for functional data defined in the 'fda' and 'funData' packages respectively. It currently supports shift, dilation and affine warping functions for functional data defined on the real line and uses the SRVF framework to handle boundary-preserving warping for functional data defined on a specific interval. Main reference for the k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment for curve clustering" <doi:10.1016/j.csda.2009.12.008>. Main reference for the SRVF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013) "Generative models for functional data using phase and amplitude separation" <doi:10.1016/j.csda.2012.12.001>.
Version: 0.4.1 Depends: R (≥ 3.5.0) Imports: cli, cluster, dbscan, fdasrvf, future.apply, ggplot2, lpSolve, nloptr, progressr, Rcpp, rlang, tibble LinkingTo: Rcpp, RcppArmadillo, nloptr Suggests: fda, funData, future, knitr, rmarkdown, testthat (≥ 3.0.0), withr Published: 2025-01-14 DOI: 10.32614/CRAN.package.fdacluster Author: Aymeric Stamm [aut, cre], Laura Sangalli [ctb], Piercesare Secchi [ctb], Simone Vantini [ctb], Valeria Vitelli [ctb], Alessandro Zito [ctb] Maintainer: Aymeric Stamm <aymeric.stamm at cnrs.fr> License: GPL (≥ 3) URL: https://astamm.github.io/fdacluster/, https://github.com/astamm/fdacluster NeedsCompilation: yes Materials: README NEWS In views: FunctionalData CRAN checks: fdacluster results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=fdacluster to link to this page.
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