Package: harbinger 1.0.787
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>.
Authors:
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harbinger.pdf |harbinger.html✨
harbinger/json (API)
# Install 'harbinger' in R: |
install.packages('harbinger', repos = c('https://cefet-rj-dal.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cefet-rj-dal/harbinger/issues
- examples_anomalies - Time series for anomaly detection
- examples_changepoints - Time series for change point detection
- examples_harbinger - Time series for event detection
- examples_motifs - Time series for change point detection
Last updated 4 months agofrom:b9f0921143. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 11 2024 |
R-4.5-win | OK | Nov 11 2024 |
R-4.5-linux | OK | Nov 11 2024 |
R-4.4-win | OK | Nov 11 2024 |
R-4.4-mac | OK | Nov 11 2024 |
R-4.3-win | OK | Nov 11 2024 |
R-4.3-mac | OK | Nov 11 2024 |
Exports:detecthan_autoencoderhanc_mlhanct_dtwhanct_kmeanshanr_arimahanr_emdhanr_fbiadhanr_ffthanr_garchhanr_histogramhanr_mlhanr_redhanr_remdhanr_wavelethar_evalhar_eval_softhar_plotharbingerhcp_amochcp_binseghcp_cf_arimahcp_cf_etshcp_cf_lrhcp_chowhcp_garchhcp_gfthcp_pelthcp_redhcp_scphdis_mphdis_saxhmo_mphmo_saxhmo_xsaxhmu_pcamastrans_saxtrans_xsax
Dependencies:audiobackportsbase64encbitopsbslibcachemcaretcaToolschangepointcheckmatechronclasscliclockclueclustercodetoolscolorspacecommonmarkcpp11crayoncurldaltoolboxdata.tabledbscandiagramdigestDistributionUtilsdoSNOWdotCall64dplyrdtwdtwcluste1071elmNNRcppEMDfansifarverfastmapfieldsflexclustFNNfontawesomeforeachforecastfracdifffsfuturefuture.applyGeneralizedHyperbolicgenericsggplot2ggrepelglobalsgluegowergplotsgtablegtoolshardhatherehhthmshtmltoolshttpuvipredisobanditeratorsjquerylibjsonliteKernelKnnkernlabKernSmoothkslabelinglaterlatticelavalifecyclelistenvlmtestlocfitlubridatemagrittrmapsMASSMatrixmclustmemoisemgcvmimeMLmetricsModelMetricsmodeltoolsmulticoolmunsellmvtnormnlmenloptrnnetnumDerivparallellypillarpkgconfigplyrpngpracmaprettyunitspROCprodlimprogressprogressrpromisesproxypurrrquadprogquantmodR6randomForestrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppThreadRcppTOMLrecipesreshapereshape2reticulateRJSONIOrlangROCRrpartrprojrootRsolnpRSpectrarugarchsandwichsassscalesshapeshinyshinyjsSkewHyperbolicsnowsourcetoolsspamspdSQUAREMstringistringrstrucchangesurvivaltibbletidyrtidyselecttimechangetimeDatetreetruncnormtseriestsmpTTRtzdburcautf8vctrsviridisLitewaveletswithrxtablextszoo