Table 4.

Key findings

1. Clustering-based outlier trajectory detection (COT) is a reliable method for outlier trajectory detection.

2. Combined detection methods for outlier measurements are preferred.

3. Some methods achieved >80% sensitivity for errors above 3 standard deviations

4. Model-based methods are reliable for errors of lower intensity.

5. Higher density favours outlier trajectory detection and model-based methods, but not time-sensitive methods.

6. Clustering and pattern analyses can be considerably affected by the presence of outliers.