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cycleTrendR  

Adaptive Cycle and Trend Analysis for Irregular Time Series
View on CRAN: Click here


Download and install cycleTrendR package within the R console
Install from CRAN:
install.packages("cycleTrendR")

Install from Github:
library("remotes")
install_github("cran/cycleTrendR")

Install by package version:
library("remotes")
install_version("cycleTrendR", "0.2.0")



Attach the package and use:
library("cycleTrendR")
Maintained by
Pietro Piu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-22
Latest Update: 2026-01-22
Description:
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>.
How to cite:
Pietro Piu (2026). cycleTrendR: Adaptive Cycle and Trend Analysis for Irregular Time Series. R package version 0.2.0, https://cran.r-project.org/web/packages/cycleTrendR. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:29), 0.2.0 (2026-01-22 10:20), 0.3.0 (2026-01-26 10:50)
Other packages that cited cycleTrendR R package
View cycleTrendR citation profile
Other R packages that cycleTrendR depends, imports, suggests or enhances
Complete documentation for cycleTrendR
Functions, R codes and Examples using the cycleTrendR R package
Full cycleTrendR package functions and examples
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