Hi, Im trying to do a forecast on some data for my group and using the Proc ESM...I do a seasonal daily model because I want it to account for changes in day of week. However, I also want to account for the month and other trends. I have one variable i'm wanting to forecast...but Im not getting as close as I want....do you have any suggestions of techniques for improving the signficance of the projected values and minimizing the errors?
Proc Sort data = cwork.forecast_queue_elig_vdps_1;
by Channel tier;
run;
ODS Listing;
ODS RTF File = '\\wfsnccicnsf01\c_cds_users\a097529\My Documents\forecastqueueEligvdps1.rtf';
proc ESM data=cwork.forecast_queue_elig_vdps_1 out = forecastedqueue_elig_vdps Lead = 15 plot=forecasts PRINT = FORECASTS;
by Channel tier;
ID trandate interval = day accumulate=average;
forecast totalqueuedin/model= seasonal;
run;
ODS rtf Close;
Thank you for your help!!!!
Allie
Allie -
Would it be possible to share your data as well?
Thanks,
Udo
how do I send data? is it safe enough to attach to here?
Hello -
Yes - if you are willing to share your data just attach it to a post.
Thanks,
Udo
Hi Allie,
In addition to Udo's request I thought i'd push you in a certain direction.
The types of multiple seasonal/cycle models can be estimated in SAS using a UCM framework. You can think of this as ESM-like but with regressors. These regressors might be continous, such as a price, or dichotomous, such as a day.
You might want to experiment a bit with the combination of seasonal length as well as some dummies for month to take care of those cycles. The dummy variable approach will require a good deal of data but as we don't know what you are working with, I'll just toss some ideas your way.
Udo, might have more to add with some data.
Regards-Ken
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