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 and a distance based on global alignment kernels 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: | 5.2.0 |
Depends: | R (≥ 3.2.0), methods, proxy (≥ 0.4-16), dtw |
Imports: | parallel, stats, utils, bigmemory, clue, cluster, dplyr, flexclust, foreach, ggplot2, ggrepel, Matrix, nloptr, RSpectra, Rcpp, RcppParallel, reshape2, rngtools |
LinkingTo: | Rcpp, RcppArmadillo, RcppParallel |
Suggests: | doParallel, knitr, parallelDist, rmarkdown, testthat, TSclust, TSdist |
Published: | 2018-01-29 |
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: | C++11, GNU make |
Materials: | NEWS |
In views: | TimeSeries |
CRAN checks: | dtwclust results |
Reference manual: | dtwclust.pdf |
Vignettes: |
Parallelization considerations for dtwclust Timing experiments for dtwclust Comparing Time-Series Clustering Algorithms in R Using the dtwclust Package |
Package source: | dtwclust_5.2.0.tar.gz |
Windows binaries: | r-devel: dtwclust_5.2.0.zip, r-release: dtwclust_5.2.0.zip, r-oldrel: dtwclust_5.2.0.zip |
OS X El Capitan binaries: | r-release: dtwclust_5.2.0.tgz |
OS X Mavericks binaries: | r-oldrel: dtwclust_5.1.0.tgz |
Old sources: | dtwclust archive |
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