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:
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