Time series clustering along with optimized techniques related
to the Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole
clustering are available. Functionality can be easily extended with
custom distance measures and centroid definitions. Implementations of
DTW barycenter averaging, a distance based on global alignment kernels,
and the soft-DTW distance and centroid routines are also provided.
All included distance functions have custom loops optimized for the
calculation of cross-distance matrices, including parallelization support.
Several cluster validity indices are included.
Version: |
6.0.0 |
Depends: |
R (≥ 3.3.0), methods, proxy (≥ 0.4-16), dtw |
Imports: |
parallel, stats, utils, clue, cluster, dplyr, flexclust, foreach, ggplot2, ggrepel, rlang, Matrix (≥ 1.5-0), RSpectra, Rcpp, RcppParallel (≥ 4.4.0), reshape2, shiny, shinyjs |
LinkingTo: |
Rcpp, RcppArmadillo, RcppParallel, RcppThread |
Suggests: |
doParallel, iterators, knitr, rmarkdown, testthat |
Published: |
2024-07-23 |
DOI: |
10.32614/CRAN.package.dtwclust |
Author: |
Alexis Sarda-Espinosa |
Maintainer: |
Alexis Sarda <alexis.sarda at gmail.com> |
BugReports: |
https://github.com/asardaes/dtwclust/issues |
License: |
GPL-3 |
Copyright: |
see file COPYRIGHTS |
URL: |
https://github.com/asardaes/dtwclust |
NeedsCompilation: |
yes |
SystemRequirements: |
GNU make |
Citation: |
dtwclust citation info |
Materials: |
NEWS |
In views: |
TimeSeries |
CRAN checks: |
dtwclust results |