sazedR: Parameter-Free Domain-Agnostic Season Length Detection in Time Series (original) (raw)
Spectral and Average Autocorrelation Zero Distance Density ('sazed') is a method for estimating the season length of a seasonal time series. 'sazed' is aimed at practitioners, as it employs only domain-agnostic preprocessing and does not depend on parameter tuning or empirical constants. The computation of 'sazed' relies on the efficient autocorrelation computation methods suggested by Thibauld Nion (2012, URL: <https://etudes.tibonihoo.net/literate_musing/autocorrelations.html>) and by Bob Carpenter (2012, URL: <https://lingpipe-blog.com/2012/06/08/autocorrelation-fft-kiss-eigen/>).
| Version: | 2.0.2 |
|---|---|
| Imports: | bspec (≥ 1.5), dplyr (≥ 0.8.0.1), fftwtools (≥ 0.9.8), pracma (≥ 2.1.4), zoo (≥ 1.8-3) |
| Published: | 2020-09-29 |
| DOI: | 10.32614/CRAN.package.sazedR |
| Author: | Maximilian Toller [aut], Tiago Santos [aut, cre], Roman Kern [aut] |
| Maintainer: | Tiago Santos |
| License: | GPL-2 |
| URL: | https://github.com/mtoller/autocorr_season_length_detection/ |
| NeedsCompilation: | no |
| Citation: | sazedR citation info |
| Materials: | README NEWS |
| In views: | TimeSeries |
| CRAN checks: | sazedR results |
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