dtw-package {dtw} | R Documentation |
Dynamic Time Warp: find the optimal alignment between two time series.
Package: | dtw |
Type: | Package |
Version: | 1.0 |
Date: | 2007-12-10 |
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
Maintainer: toni.giorgino@unipv.it
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);