TrendLSW: Wavelet Methods for Analysing Locally Stationary Time Series

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>. New users will likely want to start with the TLSW function.

Version: 1.0.2
Depends: R (≥ 4.1.0)
Imports: wavethresh, locits
Suggests: testthat (≥ 3.0.0), vdiffr
Published: 2024-04-30
DOI: 10.32614/CRAN.package.TrendLSW
Author: Euan T. McGonigle [aut, cre], Rebecca Killick [aut], Matthew Nunes [aut]
Maintainer: Euan T. McGonigle <e.t.mcgonigle at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: TrendLSW results


Reference manual: TrendLSW.pdf


Package source: TrendLSW_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): TrendLSW_1.0.2.tgz, r-oldrel (arm64): TrendLSW_1.0.2.tgz, r-release (x86_64): TrendLSW_1.0.2.tgz, r-oldrel (x86_64): TrendLSW_1.0.2.tgz
Old sources: TrendLSW archive


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