fdacluster: Joint Clustering and Alignment of Functional Data

Revisited clustering approaches to accommodate functional data by allowing to jointly align the data during the clustering process. Currently, shift, dilation and affine transformations only are available to perform alignment. The k-mean algorithm has been extended to integrate alignment and is fully parallelized. Hierarchical clustering will soon be available as well. References: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment for curve clustering" <doi:10.1016/j.csda.2009.12.008>.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: Rcpp, magrittr, tibble, dplyr, tidyr, purrr, ggplot2, nloptr
LinkingTo: Rcpp, RcppArmadillo, nloptr
Suggests: testthat
Published: 2022-05-09
Author: Laura Sangalli [aut], Piercesare Secchi [aut], Aymeric Stamm ORCID iD [cre, ctb], Simone Vantini [aut], Valeria Vitelli [aut], Alessandro Zito [ctb]
Maintainer: Aymeric Stamm <aymeric.stamm at math.cnrs.fr>
License: GPL (≥ 3)
URL: https://astamm.github.io/fdacluster/index.html, https://github.com/astamm/fdacluster
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: fdacluster results


Reference manual: fdacluster.pdf


Package source: fdacluster_0.1.1.tar.gz
Windows binaries: r-devel: fdacluster_0.1.1.zip, r-release: fdacluster_0.1.1.zip, r-oldrel: fdacluster_0.1.1.zip
macOS binaries: r-release (arm64): fdacluster_0.1.1.tgz, r-oldrel (arm64): fdacluster_0.1.1.tgz, r-release (x86_64): fdacluster_0.1.1.tgz, r-oldrel (x86_64): fdacluster_0.1.1.tgz
Old sources: fdacluster archive


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