hanr_arima: Anomaly detector using ARIMA

In harbinger: A Unified Time Series Event Detection Framework

Anomaly detector using ARIMA

Description

Fits an ARIMA model to the series and flags observations with large model residuals as anomalies. Wraps ARIMA from the forecast package.

Usage

hanr_arima()

Details

The detector estimates ARIMA(p,d,q) and computes standardized residuals. Residual magnitudes are summarized via a distance function and thresholded with outlier heuristics from harutils().

Value

hanr_arima object.

References

• Box GEP, Jenkins GM, Reinsel GC, Ljung GM (2015). Time Series Analysis: Forecasting and Control. Wiley.

Examples

library(daltoolbox)

# Load anomaly example data
data(examples_anomalies)

# Use a simple example
dataset <- examples_anomalies$simple
head(dataset)

# Configure ARIMA anomaly detector
model <- hanr_arima()

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

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

# Show detected anomalies
print(detection[(detection$event),])

harbinger documentation built on Feb. 11, 2026, 9:06 a.m.