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:	0.2.0
Depends:	R (≥ 4.1.0)
Imports:	blocklength, fANCOVA, ggplot2, lomb, gridExtra, changepoint, mgcv, dplyr, nortest, nlme, magrittr, tseries
Suggests:	testthat, knitr, rmarkdown
Published:	2026-01-22
DOI:	10.32614/CRAN.package.cycleTrendR (may not be active yet)
Author:	Pietro Piu [aut, cre]
Maintainer:	Pietro Piu <pietro.piu.si at gmail.com>
License:	GPL-3
URL:	https://github.com/PietroPiu-labstats/cycleTrendR
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	cycleTrendR results

Documentation:

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

Downloads:

Package source:	cycleTrendR_0.2.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): cycleTrendR_0.2.0.tgz, r-oldrel (x86_64): not available

Linking:

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