I am currently encountering a problem with the HoltWinters method implemented in the forecast package. If I use the method for some of my time series I have a larger error (SSE) when I use the Holt Winters with trend than without trend (Single Exponential Smoothing). As I understand, Holt Winters with trend should at least be as good as Holt Winters without trend. Can anybody explain this? I added an example below.
Best wishes,
Chris
library(forecast)
x = c(50,50,70,50,90,70,90,80,70,40,60,20,60,60,40,40,40,50,50,30,60,40,40,40,50,10,20,60,70, 60,60,80,70,80,90,80,70,30,30,80, 100,80,80,20,40,30,40,50,60,30,80, 100)
mSES = HoltWinters(x, alpha = TRUE, beta = FALSE, gamma = FALSE)
mHW = HoltWinters(x, alpha = TRUE, beta = TRUE, gamma = FALSE)
mSES$SSE
mHW$SSE
Don't set alpha or beta to TRUE. If beta is set to FALSE then it will do exponential smoothing but otherwise the input is taken as the specific parameter value. So TRUE gets coerced to be 1. So instead of letting the function choose the parameter that minimizes the SSE you are explicitly setting them to be 1.