harbinger: A Unified Time Series Event Detection Framework

By analyzing time series, it is possible to observe significant changes in the behavior of observations that frequently characterize events. Events present themselves as anomalies, change points, or motifs. In the literature, there are several methods for detecting events. However, searching for a suitable time series method is a complex task, especially considering that the nature of events is often unknown. This work presents Harbinger, a framework for integrating and analyzing event detection methods. Harbinger contains several state-of-the-art methods described in Salles et al. (2020) <doi:10.5753/sbbd.2020.13626>.

Version: 1.0.767
Imports: stats, daltoolbox, tsmp, dtwclust, rugarch, forecast, ggplot2, changepoint, strucchange, stringr, wavelets, hht, dplyr
Published: 2024-03-31
Author: Eduardo Ogasawara ORCID iD [aut, ths, cre], Antonio Castro [aut], Antonio Mello [aut], Ellen Paixão [aut], Fernando Fraga [aut], Heraldo Borges [aut], Janio Lima [aut], Jessica Souza [aut], Lais Baroni [aut], Lucas Tavares [aut], Rebecca Salles [aut], Diego Carvalho [aut], Eduardo Bezerra [aut], Rafaelli Coutinho [aut], Esther Pacitti [aut], Fabio Porto [aut], Federal Center for Technological Education of Rio de Janeiro (CEFET/RJ) [cph]
Maintainer: Eduardo Ogasawara <eogasawara at ieee.org>
License: MIT + file LICENSE
URL: https://github.com/cefet-rj-dal/harbinger, https://cefet-rj-dal.github.io/harbinger/
NeedsCompilation: no
Materials: README
CRAN checks: harbinger results

Documentation:

Reference manual: harbinger.pdf

Downloads:

Package source: harbinger_1.0.767.tar.gz
Windows binaries: r-devel: harbinger_1.0.767.zip, r-release: harbinger_1.0.767.zip, r-oldrel: harbinger_1.0.767.zip
macOS binaries: r-release (arm64): harbinger_1.0.767.tgz, r-oldrel (arm64): harbinger_1.0.767.tgz, r-release (x86_64): harbinger_1.0.767.tgz
Old sources: harbinger archive

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