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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/>).

Versions across snapshots

VersionRepositoryFileSize
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

Dependencies (latest)

Imports