Abstract
Anomalies play a critical role in statistical analysis, as their presence in data can lead to biased parameter estimation, model misspeci cation, and misleading results if classical analysis techniques are blindly applied. Additionally, anomalies can themselves be carriers of signi cant and critical information, and identifying these critical points can be the primary goal of investigations in many elds such as fraud detection, object tracking, system health monitoring, and environmental monitoring (e.g., for bush res, tsunamis, oods, earthquakes, and volcanic eruptions)
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