06-10-2013 08:49 AM
Is this what you are looking for?
sales = air;
date = intnx( 'month', '01sep78'd, _n_-1 );
format date monyy.;
proc x12 data=sales date=date;
ods select forecastCL forecastsplot;
ods output forecastCL=predicted;
BTW: this book Practical Time Series Analysis Using SAS features plenty of nice illustrations including X12.
06-11-2013 07:39 AM
thanks for your answer and the book link!
Unfortunately this statement only produces an output table with confidence limits which is called 'predicted'. What I am searching is an option to produce prediction limits instead of confidence limits.
Thanks a lot!
06-14-2013 08:14 AM
The X12 procedure (like other procedures in SAS/ETS software) uses prediction standard errors to calculate confidence intervals for future predictions (the uncertainty grows with the forecast horizon). Furthermore PROC X12 matches the Census Fortran Code - which you will find here: http://www.census.gov/srd/www/x12a/ - lots of details about the implementation can be accessed at this link.
06-24-2013 09:33 AM
Some more information was shared by the X12 R&D team, which I'm adding to this thread for documentation purposes.
In the X-12-ARIMA Reference Manual, http://www.census.gov/ts/x12a/v03/x12adocV03.pdf and X-13ARIMA-SEATS Reference Manual, http://www.census.gov/ts/x13as/docX13ASHTML.pdf section 4.7 Forecasting contains the same information:
“For a reasonably long time series, (Box and Jenkins 1976, pp. (267-269) observe that the contribution to forecast error of the error in estimating the AR and MA parameters is generally small, thus providing a justification for ignoring this source of error when computing the forecast standard errors.”
As I do not have the 1976 version of the Box and Jenkins book, I had to look for the equivalent in the 1994 version. In Chapter 9, Seasonal Models, Section 9.2.2, p. 334, I find “2. The forecasts are insensitive to small changes in parameter values such as are introduced by estimation errors.”
Chapter 9, Season Models is heavily cross-referenced with Chapter 5, Forecasting. After examining the X-12-ARIMA FORTRAN code, the standard error for the forecasts is computed as shown in 9.2.14 (5.1.16). This is just for the AR & MA error, the regression error effects are also considered in the computation. And the Ψ-weights are calculated as described in section 5.1. The Box-Jenkins reference was used for the computations apparently.
Is the customer actually getting different results? I believe that in this case, the problem is terminology. From http://robjhyndman.com/hyndsight/intervals/: “And I ask econometricians to stop being so sloppy about terminology.” The Census Bureau also uses the term “Confidence Interval”:
Although, Hyndman may find the terminology confusing, it does seem to be fairly standard practice.