*
* Example 8/2/5 from pp 413-414
*
open data adv_sale.dat
data(format=free,org=columns) 1 36 sales adv
*
boxjenk(ma=1,maxl,constant,inputs=1,define=saleseq) sales / sresids
# adv 1 1 0
*
* MA(1) process estimates for adv
*
boxjenk(ma=1,maxl,constant,define=adveq) adv / aresids
*
* Because this requires that two equations be forecasted simultaneously, we can't
* use the UFORECAST instruction, since that's just for univariate forecasts.
* Instead, we group the two equations into a MODEL, and use the FORECAST
* instruction. This produces a VECTOR of SERIES for the forecasts and another
* one for the standard errors. Because the sales equation is the second one
* listed in the group instruction, its forecasts and standard errors are
* forecasts(2) and stderrs(2).
*
group tmodel adveq saleseq
*
forecast(model=tmodel,steps=5,results=forecasts,stderrs=stderrs)
*
set lower 37 41 = forecasts(2)+stderrs(2)*%invnormal(.025)
set upper 37 41 = forecasts(2)+stderrs(2)*%invnormal(.975)
*
graph(footer="Figure 8-12 Forecasts of Sales Data",overlay=fan,ovcount=2,ovsame) 4
# sales
# forecasts(2)
# lower
# upper