C.5. Is it more appropriate to use an additive or a
multiplicative model to forecast seasonal data?
Summarize the difference(s) between these two
types of seasonal models.
Forecasting involves the act of making projections about the future performance based on both current and historical data. A forecasting model is usually selected after data has been captured for the time series. During this process, graphic and statistical techniques may be of great help. After a model has been selected, specifying the forecasting model while selecting the variables to be included is the next step (ZHU, & ZHU YI 2010).
Time series often displays seasonal behavior whereby seasonality is the tendency ...
This solution of 329 words compares the additive and multiplicative model, looking at the differences between the two models.