swh:1:snp:a42826477fed43a0b24037de7f123ff16486830d
Tip revision: 935e521fa862c893e52a85dbb72c3ae53246a8e4 authored by Toni Giorgino on 15 August 2009, 00:00:00 UTC
version 1.14-3
version 1.14-3
Tip revision: 935e521
dtw-package.Rd
\name{dtw-package}
\alias{dtw-package}
\docType{package}
\title{
Dynamic Time Warp algorithms in R
}
\description{
Dynamic Time Warp: find the optimal alignment between two time series.
}
\details{
\tabular{ll}{
Package: \tab dtw\cr
Type: \tab Package\cr
Version: \tab 1.14\cr
Date: \tab 2009-8-15\cr
License: \tab GPL-2\cr
}
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 \code{\link{stepPattern}}).
Supports windowing: none, "Itakura" parallelogram, Sakoe-Chiba band,
custom (see \code{\link{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 \code{\link{dtw}}, which is the
main entry point to the package.
If you use this software, please cite it according to
\code{citation("dtw")}. The package home page is at
\url{http://dtw.r-forge.r-project.org}.
To get the latest stable version from CRAN, use
\code{install.packages("dtw")}. To get the development version
(possibly unstable), use
\code{install.packages("dtw",repos="http://r-forge.r-project.org")}.
}
\author{
Toni Giorgino, Copyright (c) 2007-2009
Maintainer: toni.giorgino@gmail.com
}
\seealso{ \code{\link{dtw}} for the main entry point to the package;
\code{\link{dtwWindowingFunctions}} for global constraints;
\code{\link{stepPattern}} for local constraints;
\code{\link[analogue]{distance}}, \code{\link{outer}} for
building a local cost matrix with multivariate
timeseries and custom distance functions. }
\references{
Toni Giorgino. \emph{Computing and Visualizing Dynamic Time Warping
Alignments in R: The dtw Package.} Journal of Statistical
Software, 31(7), 1-24. \url{http://www.jstatsoft.org/v31/i07/}
\cr \cr
Rabiner, L. R., & Juang, B.-H. (1993). Chapter 4 in
\emph{Fundamentals of speech
recognition.} Englewood Cliffs, NJ: Prentice Hall.
}
\examples{
library(dtw);
## demo(dtw);
}
\keyword{ package }
\keyword{ ts }