For the ETS function in R, am I looking for the minimal number of data points for the forecast. I read both of the Hyndman papers (2002 & 2008) which are mentioned in the documentation, but I could not find a quantifiable value. In: http://robjhyndman.com/hyndsight/short-time-series/ he mentioned that it depends on the number of parameters . But at this point I am looking for a good source that can clarify the amount of data points needed in the ETS function. Can somebody help me with this?
Why don't you just try it and see what happens. You will find that the ets function will work with a single observation:
> 1 %>% ets %>% forecast
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
2 1 1 1 1 1
3 1 1 1 1 1
4 1 1 1 1 1
5 1 1 1 1 1
6 1 1 1 1 1
7 1 1 1 1 1
8 1 1 1 1 1
9 1 1 1 1 1
10 1 1 1 1 1
11 1 1 1 1 1
Of course, it is not fitting two parameters, but it is doing something reasonable given the information provided.
If you read the blog post you cite, I write "The only reasonable approach is to first check that there are enough observations to estimate the model, and then to test if the model performs well out-of-sample." You need more observations than parameters to actually estimate the model.