harbinger: An 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: 1.0.737
Imports: stats, daltoolbox, TSPred, tsmp, dtwclust, rugarch, forecast, ggplot2, changepoint, strucchange, stringr, dplyr, reticulate
Published: 2023-11-11
Author: Rebecca Salles [aut], Janio Lima [aut], Lais Baroni [aut], Antonio Castro [aut], Leonardo Carvalho [aut], Heraldo Borges [aut], Diego Carvalho [aut], Rafaelli Coutinho [aut], Eduardo Bezerra [aut], Esther Pacitti [aut], Fabio Porto [aut], Eduardo Ogasawara ORCID iD [aut, ths, cre], 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


Reference manual: harbinger.pdf


Package source: harbinger_1.0.737.tar.gz
Windows binaries: r-devel: harbinger_1.0.737.zip, r-release: harbinger_1.0.737.zip, r-oldrel: harbinger_1.0.737.zip
macOS binaries: r-release (arm64): harbinger_1.0.737.tgz, r-oldrel (arm64): harbinger_1.0.737.tgz, r-release (x86_64): harbinger_1.0.737.tgz, r-oldrel (x86_64): harbinger_1.0.707.tgz
Old sources: harbinger archive


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