I have panel data based on 900000 different entities with 384 time steps and the data is not normally distributed. I am looking for outliers/anomalies, this is unsupervised as I have no examples of anomalies/outliers.
Apart from clustering methods such as K-means, DBSCAN/HDBSCAN, what options do I have?
