which statistical parameters are more useful to detect anomalies and outlier? mean max min var?

This time series contains some time frame which each of them are 8K (frequencies)*151 (time samples) in 0.5 sec [overall 1.2288 millions samples per half a second)

I need to find anomalous based on different rows (frequencies) Report the rows (frequencies) which are anomalous? (an unsupervised learning method) Do you have an idea to which statistical parameter is more useful for it? mean max min median var or any parameters of these 151 sampling? Which parameter I should use? (I show one sample (151 sample per frequency) from 8k data)

Topic anomaly anomaly-detection time-series statistics machine-learning

Category Data Science


Statistical control processes and CUSUM in particular can be useful in identifying outlying values or changes in time series data.

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