Dynamic Time Warping Algorithms
ANSI/AAMI EC13 Test Waveforms, 3a and 3b
Count the number of warping paths consistent with the constraints.
Internal dtw Functions
Comprehensive implementation of Dynamic Time Warping (DTW) algorithms ...
Dynamic Time Warp
Compute a dissimilarity matrix
Plotting of dynamic time warp results
Display the cumulative cost density with the warping path overimposed
Plotting of dynamic time warp results: annotated warping function
Plotting of dynamic time warp results: pointwise comparison
Global constraints and windowing functions for DTW
Minimum Variance Matching algorithm
Step patterns for DTW
Apply a warping to a given timeseries
Compute Warping Path Area
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>.