IncDTW: Incremental Calculation of Dynamic Time Warping

The Dynamic Time Warping (DTW) distance for time series allows non-linear alignments of time series to match similar patterns in time series of different lengths and or different speeds. Beside the traditional implementation of the DTW algorithm, the specialities of this package are, (1) the incremental calculation, which is specifically useful for life data streams due to computationally efficiency, (2) the vector based implementation of the traditional DTW algorithm which is faster because no matrices are allocated and is especially useful for computing distance matrices of pairwise DTW distances for many time series and (3) the combination of incremental and vector-based calculation. C++ in the heart. For details about DTW see the original paper "Dynamic programming algorithm optimization for spoken word recognition" by Sakoe and Chiba (1978) <doi:10.1109/TASSP.1978.1163055>.

Version: 1.0.4
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.12.8), RcppParallel, ggplot2, scales, parallel, stats, data.table
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
Suggests: knitr, dtw, rmarkdown, gridExtra, testthat, dtwclust, parallelDist, microbenchmark, rucrdtw, proxy
Published: 2018-09-11
Author: Maximilian Leodolter
Maintainer: Maximilian Leodolter <maximilian.leodolter at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: IncDTW results


Reference manual: IncDTW.pdf
Vignettes: Incremental Dynamic Time Warping
Incremental Dynamic Time Warping
Package source: IncDTW_1.0.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: IncDTW_1.0.4.tgz, r-oldrel: IncDTW_1.0.4.tgz
Old sources: IncDTW archive


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