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Of course Prophet is a Python library, thus the Monty Python's Life of Brian reference: "Now you listen here. He's not the messiah. He's a very naughty boy. Now GO AWAY!" https://www.youtube.com/watch?v=3_kKAeh6qyc&ab_channel=dinge... "Yes, we are all individuals!" "Yes, we are all different!" "I'm not.": https://www.youtube.com/watch?v=KHbzSif78qQ&ab_channel=lucas... Prophets: https://www.youtube.com/watch?v=hmyuE0N…
My experience in general is that most time series model are inadequate in predicting time series except for very trivial cases of seasonalities or simple linear/nonlinear trends. I think that you can throw any model you like at the problem but all you will do is overfit most of the time.
This is to be expected, because pure time-series models (Holt-Winters, ARIMA, etc.) only capture behavior of historical data (autoregressive, i.e. yₖ = f(yₖ₋₁, yₖ₋₂, ...)). If the patterns of interest aren't primarily time-based patterns , then time series models wouldn't be predictive. In my experience, the time-series models that are reliably predictive typically aren't purely autoregressive but contain exogeneous…