I want to detect anomalies in time series data. For me an anomaly is an abnormal value over a certain period of time.
Let's say in my time series i have usually a value around 100 with small variations, e.g. a smaller value like 90 for 3 seconds. An anomaly for me would be a value of 90 for 1 minute for example.
Of course I don't want to hardcode those thresholds. Is there an unsupervised anomaly detection method, that considers not only the value (like outlier detection), but also the time dimension?