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
NeedsCompilation: no
Packaged: 2026-01-20 22:51:43 UTC; euanmcgonigle
Author: Euan T. McGonigle [aut, cre],
  Rebecca Killick [aut],
  Matthew Nunes [aut]
Repository: CRAN
Date/Publication: 2026-01-21 08:00:19 UTC
Built: R 4.6.0; ; 2026-04-26 05:05:52 UTC; unix
