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Implements Time-Weighted Dynamic Time Warping (TWDTW), a measure for quantifying time series similarity. The TWDTW algorithm, described in Maus et al. (2016) <doi:10.1109/JSTARS.2016.2517118> and Maus et al. (2019) <doi:10.18637/jss.v088.i05>, is applicable to multi-dimensional time series of various resolutions. It is particularly suitable for comparing time series with seasonality for environmental and ecological data analysis, covering domains such as remote sensing imagery, climate data, hydrology, and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, efficient 'Fortran' routines for TWDTW calculations, flexible time weighting definitions, as well as utilities for time series preprocessing and visualization.
Version: | 1.0-1 |
Imports: | Rcpp, proxy |
LinkingTo: | Rcpp |
Suggests: | rbenchmark, testthat (≥ 3.0.0) |
Published: | 2023-08-08 |
DOI: | 10.32614/CRAN.package.twdtw |
Author: | Victor Maus [aut, cre] |
Maintainer: | Victor Maus <vwmaus1 at gmail.com> |
BugReports: | https://github.com/vwmaus/twdtw/issues/ |
License: | GPL (≥ 3) |
URL: | https://github.com/vwmaus/twdtw/ |
NeedsCompilation: | yes |
Materials: | README NEWS |
In views: | TimeSeries |
CRAN checks: | twdtw results |
Reference manual: | twdtw.pdf |
Package source: | twdtw_1.0-1.tar.gz |
Windows binaries: | r-devel: twdtw_1.0-1.zip, r-release: twdtw_1.0-1.zip, r-oldrel: twdtw_1.0-1.zip |
macOS binaries: | r-release (arm64): twdtw_1.0-1.tgz, r-oldrel (arm64): twdtw_1.0-1.tgz, r-release (x86_64): twdtw_1.0-1.tgz, r-oldrel (x86_64): twdtw_1.0-1.tgz |
Old sources: | twdtw archive |
Reverse imports: | rasterdiv |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.