Answer for Reagarding ARIMA model selection

https://365datascience.com/dwqa-answer/answer-for-reagarding-arima-model-selection/ -

Hey Ganesh, 

 

Thanks for reaching out!

 

Usually finding the model is a trial-and-error approach, where you try different models to determine which fits best. Knowing if the data is stationary (no integration), or experiences no seasonal tendencies (no seasonal orders) reduces our search for the best model. 

Additionally, the ACF and PACF can give us suggestions to the number of lags to include to limit going through overly-simplistic or overly-complex models. 

 

That being said, later in the course we introduce the auto_arima method which goes through all the models with certain specifications and returns the one which fits best based on a single characteristic (the AIC).  

 

Best, 

365 Vik

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