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/>).

Getting started

Package details

AuthorMaximilian Toller [aut], Tiago Santos [aut, cre], Roman Kern [aut]
MaintainerTiago Santos <teixeiradossantos@tugraz.at>
LicenseGPL-2
Version2.0.2
URL https://github.com/mtoller/autocorr_season_length_detection/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("sazedR")

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sazedR documentation built on Oct. 23, 2020, 6:37 p.m.