cycleTrendR: Adaptive Cycle and Trend Analysis for Irregular Time Series

Provides adaptive trend estimation, cycle detection, Fourier harmonic selection, bootstrap confidence intervals, change-point detection, and rolling-origin forecasting. Supports LOESS (Locally Estimated Scatterplot Smoothing), GAM (Generalized Additive Model), and GAMM (Generalized Additive Mixed Model), and automatically handles irregular sampling using the Lomb-Scargle periodogram. Methods implemented in this package are described in Cleveland et al. (1990) <doi:10.2307/2289548>, Wood (2017) <doi:10.1201/9781315370279>, and Scargle (1982) <doi:10.1086/160554>.

Version:	0.3.0
Depends:	R (≥ 4.1.0)
Imports:	blocklength, fANCOVA, ggplot2, lomb, changepoint, mgcv, nortest, nlme, tseries
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-01-26
DOI:	10.32614/CRAN.package.cycleTrendR
Author:	Pietro Piu [aut, cre]
Maintainer:	Pietro Piu <pietro.piu.si at gmail.com>
License:	GPL-3
URL:	https://github.com/PietroPiu-labstats/cycleTrendR, https://pietropiu-labstats.github.io/cycleTrendR/
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	cycleTrendR results

Documentation:

Reference manual:	cycleTrendR.html , cycleTrendR.pdf
Vignettes:	cycleTrendR-overview (source, R code) cycleTrendR in practice (source, R code)

Downloads:

Package source:	cycleTrendR_0.3.0.tar.gz
Windows binaries:	r-devel: cycleTrendR_0.3.0.zip, r-release: cycleTrendR_0.3.0.zip, r-oldrel: cycleTrendR_0.3.0.zip
macOS binaries:	r-release (arm64): cycleTrendR_0.3.0.tgz, r-oldrel (arm64): cycleTrendR_0.3.0.tgz, r-release (x86_64): cycleTrendR_0.3.0.tgz, r-oldrel (x86_64): cycleTrendR_0.3.0.tgz
Old sources:	cycleTrendR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=cycleTrendR to link to this page.