I am trying to forecast a time series value for 2026. I have historical data from 1990 to 2016. I am using PROC AUTOREG. When I use the simple linear trend regression, I am able to get the forecast value, but when I use the logarithmic or polynomial model, the forecast values are missing. * the linear regression is ok and I can see the 2026 value in the final table PROC AUTOREG data=varfinal; model Y = TIME / method=ml nlag=5 backstep; output out=result1 predicted=Yhat pm=Ytrend lcl=Ylcl ucl=Yucl; RUN; The following 2, shows missing values after 2016 Yhat, Ytrendm, Ylcl and Yucl /**** Logarithmic ****/ PROC AUTOREG data=varfinal; model Y = TIMELOG / method=ml nlag=5 backstep; output out=result2 predicted=Yhat pm=Ytrend lcl=Ylcl ucl=Yucl; RUN; /*Polynomial */ PROC AUTOREG data=varfinal; model WIAWW = TIME TIMESQ / method=ml nlag=5 backstep; output out=result3 predicted=Yhat pm=Ytrend lcl=Ylcl ucl=Yucl; RUN; Note; TIMELOG= LOG(TIME) and TIMESQ: TIME*TIME Any help on why I can't see the forecast values in the logarithmic and polynomial case would we useful Thanks Final Note: I found the solution myself. Instead of using DATE: 1990 TO 2016, I used DATE: 1 TO 37
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