I wish to predict volume in every day , given a day,month,year, day in week (sunday/monday/...), and holiday indicator. ( total of 5 categorical variables) - base on history data of course.
basically I want to know the weight each of the variables and their values contribute to the volume.
I want to make that forcast as the volume is not necessarily spread uniqly (linear) throw the month. for example: if I'm at the begining of the month I might see a bad picture of what it may look at the end of the month.
So I'm looking for some beta-hats, or weights for the day/month/day_in_week/holiday.
will be glad to know if there is a proc that will do that.
Thanks in advance
Thanks for your answer. But the arima proc will give me the actual volume (by the forcast stament) and I only want to know the weighs of the day+month+year+ day in week+ holiday, so I can put into them my wish/ wanted volume for the future.
So the weights has to be precentage or somthing like that.
For example if I will know that Sunday has influence of 10% and my wish volume for the week is 400 and my actual volume on that Sunday was only 35 I know my volume for that day is not good. I hope I cleard myself better this time.
Both ARIMA and UCM will not only give you forecasted values, but much more.
A nice feature of UCM is that it can "decompose" forecasts into their components - which will allow you to do the "what-if" type of scenario you are talking about.
Below you will find an example - hope this helps.
*first create future values for the masonry variable of sashelp.workers;
proc esm data=sashelp.workers out=masonry plot=forecasts;
id date interval=month;
forecast masonry / method=winters;
*merge the 2 new data sets - note that for masonry it features forecasted values, which you can change later to assess the impact;
merge sashelp.workers(drop=masonry) masonry;
*run UCM with mansonry, irregular and level (which is also called trend in UCM) as compoents;
*check out the outfor data set, which features the components of the forecasts;
*outest features the parameter estimates;
proc ucm data=total plots=smooth(decomp);
id date interval=month;
forecast lead=12 outfor=outfor;
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