Learn R Programming

dtw (version 1.23-1)

Dynamic Time Warping Algorithms

Description

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) .

Copy Link

Version

Install

install.packages('dtw')

Monthly Downloads

8,751

Version

1.23-1

License

GPL (>= 2)

Maintainer

Toni Giorgino

Last Published

September 19th, 2022

Functions in dtw (1.23-1)

dtwPlotDensity

Display the cumulative cost density with the warping path overimposed
stepPattern

Step patterns for DTW
dtwWindowingFunctions

Global constraints and windowing functions for DTW
mvm

Minimum Variance Matching algorithm
warpArea

Compute Warping Path Area
dtwPlotThreeWay

Plotting of dynamic time warp results: annotated warping function
dtwPlotTwoWay

Plotting of dynamic time warp results: pointwise comparison
warp

Apply a warping to a given timeseries
dtw

Dynamic Time Warp
countPaths

Count the number of warping paths consistent with the constraints.
dtw-internal

Internal dtw Functions
dtwDist

Compute a dissimilarity matrix
dtw-package

Comprehensive implementation of Dynamic Time Warping (DTW) algorithms in R.
aami

ANSI/AAMI EC13 Test Waveforms, 3a and 3b
dtwPlot

Plotting of dynamic time warp results