A Unified Time Series Event Detection Framework

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Documentation for package ‘harbinger’ version 1.2.767

• DESCRIPTION file.

Help Pages

A1Benchmark	Yahoo Webscope S5 – A1 Benchmark (Real)
A2Benchmark	Yahoo Webscope S5 – A2 Benchmark (Synthetic)
A3Benchmark	Yahoo Webscope S5 – A3 Benchmark (Synthetic with Outliers)
A4Benchmark	Yahoo Webscope S5 – A4 Benchmark (Synthetic with Anomalies and CPs)
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 motif/discord discovery
gecco	GECCO Challenge 2018 – Water Quality Time Series
hanct_dtw	Anomaly detector using DTW
hanct_kmeans	Anomaly detector using kmeans
hanc_ml	Anomaly detector based on ML 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_fft_amoc	Anomaly Detector using FFT with AMOC Cutoff
hanr_fft_amoc_cusum	Anomaly Detector using FFT with AMOC and CUSUM Cutoff
hanr_fft_binseg	Anomaly Detector using FFT with Binary Segmentation Cutoff
hanr_fft_binseg_cusum	Anomaly Detector using FFT with BinSeg and CUSUM Cutoff
hanr_fft_sma	Anomaly Detector using Adaptive FFT and Moving Average
hanr_garch	Anomaly detector using GARCH
hanr_histogram	Anomaly detector using histograms
hanr_ml	Anomaly detector based on ML regression
hanr_remd	Anomaly detector using REMD
hanr_rtad	Anomaly and change point detector using RTAD
hanr_wavelet	Anomaly detector using Wavelets
han_autoencoder	Anomaly detector using autoencoders
harbinger	Harbinger
harutils	Harbinger Utilities
har_ensemble	Harbinger Ensemble
har_eval	Evaluation of event detection
har_eval_soft	Evaluation of event detection (SoftED)
har_plot	Plot event detection on a time series
hcp_amoc	At Most One Change (AMOC)
hcp_binseg	Binary Segmentation (BinSeg)
hcp_cf_arima	Change Finder using ARIMA
hcp_cf_ets	Change Finder using ETS
hcp_cf_lr	Change Finder using Linear Regression
hcp_chow	Chow Test (structural break)
hcp_garch	Change Finder using GARCH
hcp_gft	Generalized Fluctuation Test (GFT)
hcp_pelt	Pruned Exact Linear Time (PELT)
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
loadfulldata	Load full dataset from mini data object
mas	Moving average smoothing
mit_bih_MLII	MIT-BIH Arrhythmia Database – MLII Lead
mit_bih_V1	MIT-BIH Arrhythmia Database – V1 Lead
mit_bih_V2	MIT-BIH Arrhythmia Database – V2 Lead
mit_bih_V5	MIT-BIH Arrhythmia Database – V5 Lead
nab_artificialWithAnomaly	Numenta Anomaly Benchmark (NAB) – artificialWithAnomaly
nab_realAdExchange	Numenta Anomaly Benchmark (NAB) – realAdExchange
nab_realAWSCloudwatch	Numenta Anomaly Benchmark (NAB) realAWSCloudwatch
nab_realKnownCause	Numenta Anomaly Benchmark (NAB) realKnownCause
nab_realTraffic	Numenta Anomaly Benchmark (NAB) realTraffic
nab_realTweets	Numenta Anomaly Benchmark (NAB) realTweets
oil_3w_Type_1	Oil Wells Dataset – Type 1
oil_3w_Type_2	Oil Wells Dataset – Type 2
oil_3w_Type_4	Oil Wells Dataset – Type 4
oil_3w_Type_5	Oil Wells Dataset – Type 5
oil_3w_Type_6	Oil Wells Dataset – Type 6
oil_3w_Type_7	Oil Wells Dataset – Type 7
oil_3w_Type_8	Oil Wells Dataset – Type 8
trans_sax	SAX transformation
trans_xsax	XSAX transformation
ucr_ecg	UCR Anomaly Archive – ECG
ucr_int_bleeding	UCR Anomaly Archive – Internal Bleeding
ucr_nasa	UCR Anomaly Archive – NASA Spacecraft
ucr_power_demand	UCR Anomaly Archive – Italian Power Demand