thanks for the help in my previous post which describes my issue.
I fitted a seasonal ARIMA model to my daily temperature time series. My goal is to run the forecast lets say 10,000 times in order to get differing forecasted values, like e.g. with geometric brownian motion
Unfortunately ARIMA is deterministic and thus I receive the same output. In the end I want to have 10,000 values at each point in future time. I want to use these values to calculate a density function.
- Can bootstrapping solve this problem?
- Any other way to obtain differing values with forecast?
- Is there a way to extract values from the prediction intervals?