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>.
Documentation:
Downloads:
Reverse dependencies:
Reverse depends: |
dtwclust, mFLICA, verification, VLTimeCausality |
Reverse imports: |
CellTrails, DTWBI, dtwSat, DTWUMI, MarketMatching, mlmts, mtconnectR, NNS, sarp.snowprofile.alignment, soundgen, ssMousetrack, ts2net, TSclust, tscR, TSdist, warbleR |
Reverse suggests: |
IncDTW, parallelDist, rucrdtw |
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