Anomaly detector using FBIAD — hanr

Forward and Backward Inertial Anomaly Detector (FBIAD) detects anomalies in time series by comparing each observation against both forward and backward inertial context.

Usage

hanr_fbiad(sw_size = 30)

Arguments

sw_size: Window size for FBIAD.

Value

hanr_fbiad object.

References

Lima, J., Salles, R., Porto, F., Coutinho, R., Alpis, P., Escobar, L., Pacitti, E., Ogasawara, E. Forward and Backward Inertial Anomaly Detector: A Novel Time Series Event Detection Method. Proceedings of the International Joint Conference on Neural Networks, 2022. doi:10.1109/IJCNN55064.2022.9892088

Examples

library(daltoolbox)

# Load anomaly example data
data(examples_anomalies)

# Use a simple example
dataset <- examples_anomalies$simple
head(dataset)
#>       serie event
#> 1 1.0000000 FALSE
#> 2 0.9689124 FALSE
#> 3 0.8775826 FALSE
#> 4 0.7316889 FALSE
#> 5 0.5403023 FALSE
#> 6 0.3153224 FALSE

# Configure FBIAD detector
model <- hanr_fbiad()

# Fit the model
model <- fit(model, dataset$serie)

# Run detection
detection <- detect(model, dataset$serie)

# Show detected anomalies
print(detection[(detection$event),])
#>    idx event    type
#> 50  50  TRUE anomaly