Hyperparameter-free method for Moving Average/ Exponential smoothing?

Asked Jun 20 '19 at 02:26

Active Jan 13 '21 at 10:55

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I want to find hyperparameter-free method for Moving Average/ Exponential smoothing. Is there any related paper or python code?

S(t)= alpha * F(t) + (1-alpha) * S(t-1)

Any methods can avoid the choice of alpha? Or automatically update the alpha?

Thank you.

asked Jun 20 '19 at 02:26

user145177

Related: Question about the weighting factor of Exponential Weighted Moving Average (EWMA/EMA). – Richard Hardy Jun 20 '19 at 09:16
I think most of the exponential smoothing functions will estimate the $\alpha$ for you. Otherwise it is extremely easy to write your own code for an exponential smoother for a given $\alpha$; estimation of $\alpha$ is the hard part. Try out function ets from the forecast package in R. It estimates $\alpha$ and even facilitates (optionally) automated selection between different versions of exponential smoothing methods. – Richard Hardy Jun 20 '19 at 09:18
Ok, thank you so much. I will try it now. – user145177 Jun 20 '19 at 10:58
you can use pd.ewm(alpha=#your choice#) – Satyaki KC Jan 13 '21 at 10:55

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