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: <>) and by Bob Carpenter (2012, URL: <>).

Getting started

Package details

AuthorMaximilian Toller [aut], Tiago Santos [aut, cre], Roman Kern [aut]
MaintainerTiago Santos <[email protected]>
Package repositoryView on CRAN
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sazedR documentation built on May 2, 2019, 1:46 p.m.