Parameter-Free Domain-Agnostic Season Length Detection in Time Series
Compute the AZE component of the SAZED ensemble
Compute the AZED component of the SAZED ensemble
Compute and shorten autocorrelation
Downsample Time Series
Preprocess Time Series for SAZED ensemble
Compute the S component of the SAZED ensemble
Compute the SA component of the SAZED ensemble
SAZED Ensemble (Majority)
SAZED Ensemble (Optimum)
sazedR: A package for for estimating the season length of a seasonal t...
Compute the ZE component of the SAZED ensemble
Compute the ZED component of the SAZED ensemble
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/>).