dtw: Dynamic Time Warping Algorithms

A comprehensive implementation of dynamic time warping (DTW) algorithms in R. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc., as described in Giorgino (2009) <doi:10.18637/jss.v031.i07>.

Version: 1.23-1
Depends: R (≥ 2.10.0), proxy
Imports: graphics, grDevices, stats, utils
Published: 2022-09-19
DOI: 10.32614/CRAN.package.dtw
Author: Toni Giorgino [aut, cre]
Maintainer: Toni Giorgino <toni.giorgino at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://dynamictimewarping.github.io/, http://dtw.r-forge.r-project.org/
NeedsCompilation: yes
Citation: dtw citation info
Materials: ChangeLog
In views: TimeSeries
CRAN checks: dtw results


Reference manual: dtw.pdf
Vignettes: Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package


Package source: dtw_1.23-1.tar.gz
Windows binaries: r-devel: dtw_1.23-1.zip, r-release: dtw_1.23-1.zip, r-oldrel: dtw_1.23-1.zip
macOS binaries: r-release (arm64): dtw_1.23-1.tgz, r-oldrel (arm64): dtw_1.23-1.tgz, r-release (x86_64): dtw_1.23-1.tgz, r-oldrel (x86_64): dtw_1.23-1.tgz
Old sources: dtw archive

Reverse dependencies:

Reverse depends: dtwclust, verification, VLTimeCausality
Reverse imports: CellTrails, ddc, DTWBI, DTWUMI, MarketMatching, pGRN, rplanes, sarp.snowprofile.alignment, soundgen, squat, ssMousetrack, TSclust, TSdist, warbleR
Reverse suggests: IncDTW, parallelDist, rucrdtw


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