I have a set of data that I am currently analysing.
I am having difficulty in deciding whether an Additive model should be used to forecast the data, or if I should use a Multiplicative model.
I know the difference between the two, and I can apply the correct model when the raw data is linear...but in this case, my data is non linear.
I have attached a time-series of my data - which of the two models should I use and why?
(My instinct is to go with the Additive Model on the basis that the magnitude of the seasonal fluctuations (or the variation around the trend-cycle) doesn't appear to vary with the level of the time series.