sazedR: Parameter-Free Domain-Agnostic Season Length Detection in Time Series
Maximilian Toller, Tiago Santos, Roman Kern · 2018
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: ) and by Bob Carpenter (2012, URL: ).