Hello -
All time series based forecasting methods have a similar requirement for the ID variable (date or datetime information): it needs to be complete, with other words missing values in the time ID are not allowed. As such you will have to fill in these gaps for the time ID - for example by using PROC TIMESERIES:
data have;
set sashelp.air;
if date="01JAN57"d then delete;
if date="01SEP59"d then delete;
run;
proc timeseries data=have out=want;
id date interval=month accumulate=total;
var air;
run;
One the time id is intact, for UCM the following holds true (from documentation): "Embedded missing values in the dependent variable usually cause no problems in UCM modeling. However, no embedded missing values are allowed in the predictor variables."
Depending on your business question at hand you may want to impute missing values of the dependent varialbe using PROC TIMESERIES for example (see setmissing option).
Thanks,
Udo