You can use the cmovave transformation operation in PROC EXPAND:
proc expand data=have out=want;
by zone;
id time;
convert demand = avg / transform=(cmovave 3);
run;
If you want a pure DATA step approach, you can calculate a lag and lead, then divide. Attached is a program that will let you calculate leads efficiently.
%lead(data=have, out=have_lead, var=demand, by=zone);
data want;
set have_lead;
by zone time;
lag1_demand = lag(demand);
/* Calculate the denominator and do not set lags for the first value of zone */
if(first.zone) then do;
n = 1;
lag1_demand = .;
end;
else n = 3 - nmiss(lag1_demand, lead1_demand);
avg = sum(demand, lag1_demand, lead1_demand)/n;
drop lag1_demand lead1_demand n;
run;
Don't miss out on SAS Innovate - Register now for the FREE Livestream!
Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.