A Unified Time Series Event Detection Framework

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Documentation for package ‘harbinger’ version 1.1.707

• DESCRIPTION file.

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detect	Detect events in time series
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
hanct_dtw	Anomaly detector using DTW
hanct_kmeans	Anomaly detector using kmeans
hanc_ml	Anomaly detector based on machine learning classification
hanr_arima	Anomaly detector using ARIMA.
hanr_emd	Anomaly detector using EMD
hanr_fbiad	Anomaly detector using FBIAD
hanr_fft	Anomaly detector using FFT
hanr_garch	Anomaly detector using GARCH
hanr_histogram	Anomaly detector using histogram
hanr_ml	Anomaly detector based on machine learning regression.
hanr_red	Anomaly and change point detector using RED
hanr_remd	Anomaly detector using REMD
hanr_wavelet	Anomaly detector using Wavelet
han_autoencoder	Anomaly detector using autoencoder
harbinger	Harbinger
harutils	Harbinger Utils
har_ensemble	Harbinger Ensemble
har_eval	Evaluation of event detection
har_eval_soft	Evaluation of event detection
har_plot	Plot event detection on a time series
hcp_amoc	At most one change (AMOC) method
hcp_binseg	Binary segmentation (BinSeg) method
hcp_cf_arima	Change Finder using ARIMA
hcp_cf_ets	Change Finder using ETS
hcp_cf_lr	Change Finder using LR
hcp_chow	Chow test method
hcp_garch	Change Finder using GARCH
hcp_gft	Generalized Fluctuation Test (GFT)
hcp_pelt	Pruned exact linear time (PELT) method
hcp_red	Anomaly and change point detector using RED
hcp_scp	Seminal change point
hdis_mp	Discord discovery using Matrix Profile
hdis_sax	Discord discovery using SAX
hmo_mp	Motif discovery using Matrix Profile
hmo_sax	Motif discovery using SAX
hmo_xsax	Motif discovery using xsax
hmu_pca	Multivariate anomaly detector using PCA
mas	Moving average smoothing
trans_sax	SAX
trans_xsax	XSAX