turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

- Home
- /
- Analytics
- /
- Stat Procs
- /
- ARMA prediction: White Noise inputs

Topic Options

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

05-08-2013 10:14 PM

Hi All,

I have the following time series model for prediction purposes

**Loss_t = b1* Loss_(t-1) + b2*GDP_t + b3*W_(t-1)** where W_t is the usual white noise variable.

So this is similar to ARMA(1,1) except that it also contains an extra predictor, GDP at time t.

I have only 20 observations on each variable except GDP for which I know till 100 values.

For predicting say, the 22nd value for Loss (i.e.Loss_22), how do I input the value of the W_21 variable, because this variable (W_21) is generally proxied via the error in prediction (i.e. observed - predicted value of Loss) in the 21st stage, but since I don't know the observed value of Y_21, there is no way to calculate the error in this stage (21st) .

Also, the way I have calculated the coefficients in the above model is non-standard (differencing, bootstrapping, ridge regression), hence I cannot use the general ARMA codes in SAS for prediction.

So it would be great if you could help on this method or let me know what algorithm SAS uses to solve this problem.

Appreciate your help.

Thanks,

Preetam

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to preetampal

05-10-2013 03:30 PM

Hi Preetam,

If you post this in the Forecasting forum, the people there are much more apt to be able to give you a good answer.

Steve Denham