fdacluster: Joint Clustering and Alignment of Functional Data
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
SRSF 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 SRSF 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: |
0.3.0 |
Depends: |
R (≥ 3.5.0) |
Imports: |
cli, cluster, dbscan, dplyr, fdasrvf, forcats, furrr, ggplot2, lpSolve, nloptr, progressr, purrr, Rcpp, rlang, tibble, tidyr, withr |
LinkingTo: |
Rcpp, RcppArmadillo, nloptr |
Suggests: |
fda, funData, future, knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: |
2023-07-04 |
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/index.html,
https://github.com/astamm/fdacluster |
NeedsCompilation: |
yes |
Materials: |
README NEWS |
In views: |
FunctionalData |
CRAN checks: |
fdacluster results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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