We've seen three methods so far: simple exponential smoothing for trend-less data, double exponential smoothing (also known as Holt's linear method) for a linear or damped trend component, and triple exponential smoothing (or Holt–Winters) for additive or multiplicative seasonality.
In a taxonomy of these methods first proposed in 1969 and expanded/refined in an important 2001 paper by Rob Hyndman (the author of the forecast package) et al., these methods can be nicely summarized in a table such as this:
Seasonal component
| Trend component | None | Additive | Multiplicative |
| None | NN | NA | NM |
| Additive | AN | AA | AM |
| Additive Damped | DN | DA | DM |
| Multiplicative | MN | MA | MM |
This taxonomy encompasses all popular exponential...
