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)
collect_batch_log       Collect batch execution log
collect_detection       Collect final detection output
collect_trace           Collect the online trace
detect                  Detect events in time series
detect.har_ensemble_fuzzy
                        Detect events using Harbinger Fuzzy Ensemble
evaluate.har_stream_eval
                        Evaluate a streaming trace
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
fit.har_online_session
                        Fit an online session
gecco                   GECCO Challenge 2018 – Water Quality Time
                        Series
han_autoencoder         Anomaly detector using autoencoders
hanc_ml                 Anomaly detector based on ML classification
hanct_dtw               Anomaly detector using DTW
hanct_kmeans            Anomaly detector using k-means
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               Resilient Transformation Anomaly Detector
                        (RTAD)
hanr_wavelet            Anomaly detector using Wavelets
har_ensemble            Harbinger Ensemble
har_ensemble_fuzzy      Harbinger Fuzzy Ensemble
har_ensemble_plot       Plot Harbinger Ensemble Outputs
har_ensemble_plot_models
                        Plot individual model detections in a Harbinger
                        fuzzy ensemble
har_eval                Evaluation of event detection
har_eval_soft           Evaluation of event detection (SoftED)
har_memory_full         Full memory policy
har_memory_last_observations
                        Last-observation memory policy
har_memory_sliding      Sliding batch memory policy
har_online_detect_only
                        Detect-only execution strategy
har_online_executor     Online execution strategies
har_online_incremental
                        Incremental execution strategy
har_online_memory       Online memory policies
har_online_refit_full   Full refit execution strategy
har_online_session      Harbinger online session
har_online_sources      Streaming data sources for Harbinger
har_plot                Plot event detection on a time series
har_source_callback     Callback source
har_source_dataframe    Data-frame source
har_source_kafka        Kafka source stub
har_source_simulated    Simulated source
har_stream_eval         Streaming evaluation for online detection
har_stream_experiment   Streaming experiment runner
harbinger               Harbinger
harutils                Harbinger Utilities
hcp_amoc                At Most One Change (AMOC)
hcp_binseg              Binary Segmentation (BinSeg)
hcp_bocpd               Bayesian Online Change Point Detection
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_joinpoint           Joinpoint Regression++ change-point detector
hcp_kswin               KSWIN change-point detector
hcp_page_hinkley        Page-Hinkley change-point detector
hcp_pelt                Pruned Exact Linear Time (PELT)
hcp_scp                 Seminal change point
hcp_waypoint            Waypoint: adaptive change-point detection with
                        autoencoder and CUSUM
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
ingest                  Add observations to an online session
is_finished             Test whether an online session has finished
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_realAWSCloudwatch   Numenta Anomaly Benchmark (NAB)
                        realAWSCloudwatch
nab_realAdExchange      Numenta Anomaly Benchmark (NAB) –
                        realAdExchange
nab_realKnownCause      Numenta Anomaly Benchmark (NAB) realKnownCause
nab_realTraffic         Numenta Anomaly Benchmark (NAB) realTraffic
nab_realTweets          Numenta Anomaly Benchmark (NAB) realTweets
next_observation        Get the next observation from a source
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
run_online              Run an online session
source_info             Retrieve source metadata
step_online             Step an online session once
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
