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I need to do sales forecasting.My historical data shows stationary pattern & present of trend,Seasonality & cyclic pattern. I would like to check with you that how to select between Holt Winters and ARIMA to decide the method to be used for future prediction?

Thanks

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    $\begingroup$ The Holt Winter's forecasting method is simple exponential smoothing which is a special case of ARIMA models, namely the IMA(0,1,1) model. $\endgroup$
    – Michael R. Chernick
    Commented Feb 14, 2017 at 14:20
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    $\begingroup$ To be more precise, I would say either ARIMA(0,1,1) or IMA(1,1) since the zero in IMA(0,1,1) indexes the AR order that is excluded from the model name. R Learner, check also earlier threads on the subject; similar questions have been asked before. E.g. this would be a duplicate, but it does not have a good answer. Hmm, so probably we still need an answer to this one. $\endgroup$
    – Richard Hardy
    Commented Feb 14, 2017 at 19:45
  • $\begingroup$ @RichardHardy: do you want to post your comment(s) as an answer? Better to have a short answer than no answer at all. Anyone who has a better answer can post it. $\endgroup$
    – Stephan Kolassa
    Commented Sep 18, 2019 at 11:33
  • $\begingroup$ @StephanKolassa, I do not think my comment constitutes an answer to the actual question (about model selection for forecasting). Rather, it is more of a clarification regarding terminology. $\endgroup$
    – Richard Hardy
    Commented Sep 18, 2019 at 11:46
  • $\begingroup$ @RichardHardy: I think it's as close as we will get to an answer to this question... I'll post a short answer. $\endgroup$
    – Stephan Kolassa
    Commented Sep 18, 2019 at 11:50

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As Michael Chernick and Richard Hardy point out, there are relationships between Exponential Smoothing and ARIMA models that essentially mean that the forecasts won't differ by much (differences mainly driven by choices in the initialization).

I would recommend that you run a holdout test and choose the method that performs best on a holdout sample. This may be helpful.

(See here for a motivation for short answers. Longer answers are always welcome.)

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  • $\begingroup$ I actually did not (intend to) express a thought that the forecasts won't differ by much. Probably they would, given that ARIMA can model a rather rich selection of patterns (unlike HW which is rather specific). $\endgroup$
    – Richard Hardy
    Commented Sep 18, 2019 at 12:27
  • $\begingroup$ @RichardHardy: yes, it depends on whether auto.arima() (or whatever) actually chooses an ARIMA model that is equivalent to a smoothing one. I still think that there is little to choose between them in terms of forecasting accuracy. To be honest, in sales forecasting, data cleansing and correct modeling of demand drivers is usually far more important than choosing between ARIMA and Smoothing. $\endgroup$
    – Stephan Kolassa
    Commented Sep 18, 2019 at 12:30
  • $\begingroup$ Given your experience, you certainly know what you are talking about, so no objections. $\endgroup$
    – Richard Hardy
    Commented Sep 18, 2019 at 12:44

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