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sazedR: Parameter-Free Domain-Agnostic Season Length Detection in Time Series
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/>).
Getting started
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Package details |
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| Author | Maximilian Toller [aut], Tiago Santos [aut, cre], Roman Kern [aut] |
| Maintainer | Tiago Santos <teixeiradossantos@tugraz.at> |
| License | GPL-2 |
| Version | 2.0.2 |
| URL | https://github.com/mtoller/autocorr_season_length_detection/ |
| Package repository | View on CRAN |
| Installation |
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