Here is my current process:
x.sub<- subset(Model.Update, Row <200& Row >0) # INITIAL SAMPLE
x.sub1<-subset(Model.Update, Row <206& Row >200) # Subset into lots of 5
until current period - 5 period
...
update frequency
x.subn<-subset(Model.Update, Row <XXX & Row >XXX)
# Run regressions
A1<-lm(y ~ x + z, data=x.sub) # Will forecast 200 to 205
A2<-lm(y ~ x + z, data=x.sub1) # will forecast 206 to 210
...
An<-lm(y ~ x + z, data=x.subn)
name<-predict(A1,x.sub1) # Make predictions for subset
...
namen<-predict(An,x.subn)
Then export to excel.
write.csv(name,file="1.csv")
write.csv(namen,file="n.csv")
Seems like there must be an easier way then creating hundreds of subsets. I
build all my lines in excel, concatenate, then copy and paste into R to save
time.
Cheers
Steve
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