1
$\begingroup$

I am working with time series values which are all in the closed interval [0, 1]; these values represent relative frequencies, i.e., empirical probabilities. I would like to create a model such that all forecasted values are within [0, 1], but it would also be fine if the model's output was strictly within the open interval (0, 1).

This answered question tackles the lower bound aspect of my question, but not the upper bound aspect: How to achieve strictly positive forecasts?

I'd like to use the R forecast package if possible to achieve this, but I am open to other suggestions.

$\endgroup$
3
  • $\begingroup$ May be time series logistic regression. I have not personally applied it, but I have come across in couple of instances in this website. $\endgroup$
    – forecaster
    Jul 14, 2014 at 1:04
  • 2
    $\begingroup$ See robjhyndman.com/hyndsight/forecasting-within-limits $\endgroup$ Jul 14, 2014 at 3:57
  • $\begingroup$ Prof. Hyndman, thank you for the clarification and for the forecast package! $\endgroup$ Jul 14, 2014 at 12:46

1 Answer 1

3
$\begingroup$

Prof. Hyndman points out this approach in his comment above:

"...trans­form the data using a scaled logit trans­form which maps (a,b) to the whole real line:

$$y = \log\left(\frac{x-a}{b-x}\right)$$

where x is on the orig­i­nal scale and y is the trans­formed data."

See: http://robjhyndman.com/hyndsight/forecasting-within-limits/

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.