ARIMA parameter configuration p, q, d
hi,
I am fairly new to data science and exploring timeseries. I'm currently trying the ARIMA model but notice there is a big difference in the outcome of the model by configuring the p, q and d parameters. Is there anyone who can explain in simple words what each parameter means and how I can come up with the best configuration? Or should I use the default and use a parameter optimization?
I hope someone can share his/her experience.
Thanks,
Bart
I am fairly new to data science and exploring timeseries. I'm currently trying the ARIMA model but notice there is a big difference in the outcome of the model by configuring the p, q and d parameters. Is there anyone who can explain in simple words what each parameter means and how I can come up with the best configuration? Or should I use the default and use a parameter optimization?
I hope someone can share his/her experience.
Thanks,
Bart
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MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,507 RM Data ScientistHi @Barclaeys ,p and q are basically how far the model can look back. Keep i mind that ARIMA has three parts (AutoRegressive, Integral and Moving Average). p is the look back for the AR part, q for the MA part. If you set for example p=1 and q=0, then your model will only be autoregressive and only consider the last data point.On d: that controls the I part of ARIMA. In layman terms: ARIMA can forecast not just the time series itself, but alternatively it's derivative (and then later integrate again). if you set d=0 you forecast the original series, d=1 the 1st derivative and so on. I usually only try d=0 and d=1.Best,Martin
 Sr. Director Data Solutions, Altair RapidMiner 
Dortmund, Germany5
Answers
Thanks, Bart
Dortmund, Germany