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.

Maintainer: Alexis Sarda <alexis.sarda at gmail.com>

Author(s): Alexis Sarda-Espinosa

Install package and any missing dependencies by running this line in your R console:

install.packages("dtwclust")

Depends R (>= 3.2.0), proxy(>=0.4-16), clue, dtw, ggplot2
Imports methods, parallel, stats, utils, caTools, flexclust, foreach, Rcpp, reshape2, rngtools
Suggests TSdist, TSclust, cluster, doParallel, testthat, knitr
Enhances
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Package dtwclust
Materials
URL https://github.com/asardaes/dtwclust
Task Views TimeSeries
Version 3.1.1
Published 2017-02-12
License GPL-3
BugReports https://github.com/asardaes/dtwclust/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks dtwclust check results
Package source dtwclust_3.1.1.tar.gz