Anomaly detector using FBIAD
Value
hanr_fbiad object Forward and Backward Inertial Anomaly Detector (FBIAD) detects anomalies in time series. Anomalies are observations that differ from both forward and backward time series inertia doi:10.1109/IJCNN55064.2022.9892088.
Examples
library(daltoolbox)
#loading the example database
data(examples_anomalies)
#Using simple example
dataset <- examples_anomalies$simple
head(dataset)
#> serie event
#> 1 1.0000000 FALSE
#> 2 0.9689124 FALSE
#> 3 0.8775826 FALSE
#> 4 0.7316889 FALSE
#> 5 0.5403023 FALSE
#> 6 0.3153224 FALSE
# setting up time series regression model
model <- hanr_fbiad()
# fitting the model
model <- fit(model, dataset$serie)
detection <- detect(model, dataset$serie)
# filtering detected events
print(detection[(detection$event),])
#> idx event type
#> 50 50 TRUE anomaly