R Observatory: Metrics for TrendLSW version 1.0.6

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

TrendLSW

1.0.6

Wavelet Methods for Analysing Locally Stationary Time Series

0packages depend

2.8Kdownloads / year

84.6%test coverage

13/13checks pass

Overview

About

Maintained by Euan T. McGonigleFirst published 2024-04-224 releasesCRAN page ↗GitHub ↗

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.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("TrendLSW", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("EuanMcGonigle/TrendLSW")

Development version from EuanMcGonigle/TrendLSW. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-trendlsw

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-TrendLSW

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-TrendLSW

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 1.3 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 2.19

84.6%

Coverage · measured lines

100%

Documentation · exports

2

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 153 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 98%
Return-value docs: 100%
References docs: 88%

Downloads

2.8K

CRAN downloads in the past year

Rank #17,025 · ~8/day · ~233/mo

Releases R versions

Daily download trend is not available in this view yet.

18630 days

62890 days

2.8K1 year

Compare downloads with other packages →

Also on141 r2u23 autocran

Repository

GitHub ↗ euanmcgonigle/trendlsw

1Stars

0Forks

0Open issues

0Open PRs

3Releases

537Commits

2Contributors

crannonparametric-regressionspectral-analysisspectrumtime-serieswaveletsr-packagetime-series-analysis

537 commits · Last activity 2026-08-07

Stars over time

2023-06-28 · 12026-07-07 · 1

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/euanmcgonigle/trendlsw on 2026-08-16.

Continuous integration (1)

GitHub Actions

CRAN release process (1)

CRAN-SUBMISSION

Docs source (1)

README.Rmd

Lint, format, editor (1)

RStudio project

Show all practices

Coverage (1)

Codecov

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Depends (1)

R >= 4.1.0

Imports (2)

wavethresh locits

LinkingTo (0)

none

Suggests (2)

testthat vdiffr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (3)

Maintainer (1)

Euan T. McGonigle

Author, Maintainer

Authors (3)

Euan T. McGonigle

Author, Maintainer

Rebecca Killick

Author

Matthew Nunes

Author

Package Timeline

4 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
1.0.6Latest
2026-01-21 · current release · diff ↗
1.0.4
2025-11-24 · diff ↗
R
R 4.5.0 released · 2025-04-11
1.0.2
2024-04-30 · diff ↗
R
R 4.4.0 released · 2024-04-24
1.0.1
2024-04-22
R
R 4.3.0 released · 2023-04-21

Package metadata

First published: 2024-04-22
Total releases: 4 / 2 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.1.0
Bundled data: 18 KB / 3 files
Download size: 319 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Time Series Analysis

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("TrendLSW")

Format

McGonigle, E. T., Killick, R., & Nunes, M. (2026). TrendLSW: Wavelet Methods for Analysing Locally Stationary Time Series (Version 1.0.6) [Computer software]. https://doi.org/10.32614/CRAN.package.TrendLSW

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for TrendLSW version 1.0.6 [Data set]. HJJB, LLC. Data release v2026-08-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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