I am trying to forecast a large set of time series that feature very different characteristics. The figure below shows three exemplary series:
My first idea was to identify periodical repetitions as they are present in the upmost subplot. For this I followed the advice from this answer. I hoped that for very periodic data I would find significant peaks in the power spectrum of the time series and could thus distinguish between series with and without repetitive patterns.
However when I used the scipy's
periodogram function on the data I was not able to get a distinctive difference for the three example time series, as shown in the following figures:
Periodogram of time series #1:
Periodogram of time series #2:
Periodogram of time series #3:
What different method can I use to identify periodic patterns and utilize this information to optimize forecasting?