This must come up---the forecasting of things that are stuck between 0 and 1.
In my series, I suspect an auto-regression component, and also a mean-reverting component, so I want something that I can interpret like an ARIMA---but I don't want it to shoot off to 1000% in the future.
Do you just use an ARIMA model as the parameter in a logistic regression to confine the result between 0 and 1?
Or I learned here that Beta regressions are more appropriate for (0,1) data. How would I apply this to a time series? Are there good R packages or Matlab functions that make fitting and forecasting this easy?