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 
[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 |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=fdacluster
to link to this page.