| dtw-package {dtw} | R Documentation |
Dynamic Time Warp: find the optimal alignment between two time series.
| Package: | dtw |
| Type: | Package |
| Version: | 1.14 |
| Date: | 2009-8-15 |
| License: | GPL-2 |
Comprehensive implementation of Dynamic Time Warping (DTW) algorithms in R.
DTW finds the optimal (least cumulative distance) mapping between a given query into a given reference time series.
Most variants of the algorithm are supported: symmetric, asymmetric and
custom step patterns, with weighting (see stepPattern).
Supports windowing: none, "Itakura" parallelogram, Sakoe-Chiba band,
custom (see dtwWindowingFunctions). Handles query and
reference of arbitrary lengths. Multivariate matching and arbitrary
definition for a distance function are supported via user-supplied local
distance matrix. The Minimum Variance Matching algorithm is also
supported, as a special case of DTW.
Package provides minimum cumulative distance, warping function, plots, etc. A fast, compiled version of the algorithm is normally used. Should it not be available, a slower pure-R equivalent is automatically used as a fall-back.
Please see documentation for function dtw, which is the
main entry point to the package.
If you use this software, please cite it according to
citation("dtw"). The package home page is at
http://dtw.r-forge.r-project.org.
To get the latest stable version from CRAN, use
install.packages("dtw"). To get the development version
(possibly unstable), use
install.packages("dtw",repos="http://r-forge.r-project.org").
Toni Giorgino, Copyright (c) 2007-2009
Maintainer: toni.giorgino@gmail.com
Toni Giorgino. Computing and Visualizing Dynamic Time Warping
Alignments in R: The dtw Package. Journal of Statistical
Software, 31(7), 1-24. http://www.jstatsoft.org/v31/i07/
Rabiner, L. R., & Juang, B.-H. (1993). Chapter 4 in
Fundamentals of speech
recognition. Englewood Cliffs, NJ: Prentice Hall.
dtw for the main entry point to the package;
dtwWindowingFunctions for global constraints;
stepPattern for local constraints;
distance, outer for
building a local cost matrix with multivariate
timeseries and custom distance functions.
library(dtw); ## demo(dtw);