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/>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.2 |
rolling linux/jammy R-4.5 | sazedR_2.0.2.tar.gz |
40.7 KiB |
2.0.2 |
rolling linux/noble R-4.5 | sazedR_2.0.2.tar.gz |
40.7 KiB |
2.0.2 |
rolling source/ R- | sazedR_2.0.2.tar.gz |
6.4 KiB |
2.0.2 |
latest linux/jammy R-4.5 | sazedR_2.0.2.tar.gz |
40.7 KiB |
2.0.2 |
latest linux/noble R-4.5 | sazedR_2.0.2.tar.gz |
40.7 KiB |
2.0.2 |
latest source/ R- | sazedR_2.0.2.tar.gz |
6.4 KiB |
2.0.2 |
2026-04-26 source/ R- | sazedR_2.0.2.tar.gz |
6.4 KiB |
2.0.2 |
2026-04-23 source/ R- | sazedR_2.0.2.tar.gz |
6.4 KiB |
2.0.2 |
2026-04-09 windows/windows R-4.5 | sazedR_2.0.2.zip |
43.7 KiB |
2.0.2 |
2025-04-20 source/ R- | sazedR_2.0.2.tar.gz |
6.4 KiB |