Package: twdtw
Title: Time-Weighted Dynamic Time Warping
Version: 1.0-2
Authors@R: 
    c(
      person(
        given = "Victor", 
        family = "Maus", 
        role = c("aut", "cre"),
        email = "vwmaus1@gmail.com",
        comment = c(ORCID = "0000-0002-7385-4723")
      )
    )
Description: 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.
License: GPL (>= 3)
URL: https://github.com/vwmaus/twdtw/
BugReports: https://github.com/vwmaus/twdtw/issues/
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: Rcpp, proxy
Suggests: rbenchmark, testthat (>= 3.0.0)
LinkingTo: Rcpp
Collate: 'RcppExports.R' 'convert_date_to_numeric.R' 'init.R'
        'plot_cost_matrix.R' 'twdtw.R' 'zzz.R'
Config/testthat/edition: 3
Repository: https://vwmaus.r-universe.dev
Date/Publication: 2023-12-26 13:10:02 UTC
RemoteUrl: https://github.com/vwmaus/twdtw
RemoteRef: HEAD
RemoteSha: d740a38151cc25b419683bb33c6234935ff34efc
NeedsCompilation: yes
Packaged: 2026-07-03 17:10:21 UTC; root
Author: Victor Maus [aut, cre] (ORCID: <https://orcid.org/0000-0002-7385-4723>)
Maintainer: Victor Maus <vwmaus1@gmail.com>