Package: TrendLSW
Type: Package
Title: Wavelet Methods for Analysing Locally Stationary Time Series
Version: 1.0.6
Authors@R: c(person("Euan T.", "McGonigle", email="e.t.mcgonigle@soton.ac.uk",role=c("aut", "cre")),
        person("Rebecca","Killick", role="aut"),
        person("Matthew","Nunes", role="aut"))
Depends: R (>= 4.1.0)
Maintainer: Euan T. McGonigle <e.t.mcgonigle@soton.ac.uk>
Description: Fitting models for, and simulation of, trend locally
        stationary wavelet (TLSW) time series models, which take
        account of time-varying trend and dependence structure in a
        univariate time series. The TLSW model, and its estimation, is
        described in McGonigle, Killick and Nunes (2022a)
        <doi:10.1111/jtsa.12643>, (2022b) <doi:10.1214/22-EJS2044>.
        Further information regarding the use of the package, along
        with detailed examples, can be found in McGonigle, Killick and
        Nunes (2025) <doi:10.18637/jss.v115.i10>. New users will likely
        want to start with the TLSW function.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: wavethresh, locits
URL: https://github.com/EuanMcGonigle/TrendLSW
BugReports: https://github.com/EuanMcGonigle/TrendLSW/issues
RoxygenNote: 7.3.2
Suggests: testthat (>= 3.0.0), vdiffr
Config/testthat/edition: 3
Config/pak/sysreqs: libglpk-dev libxml2-dev
Repository: https://euanmcgonigle.r-universe.dev
Date/Publication: 2026-08-07 09:21:38 UTC
RemoteUrl: https://github.com/euanmcgonigle/trendlsw
RemoteRef: HEAD
RemoteSha: 2f1bc31abf8d10a101c023d63e7bf3ac8e9ca02c
NeedsCompilation: no
Packaged: 2026-10-06 10:59:39 UTC; root
Author: Euan T. McGonigle [aut, cre],
  Rebecca Killick [aut],
  Matthew Nunes [aut]