[R] n step ahead forecasts

From: sj <ssj1364_at_gmail.com>
Date: Wed 24 Jan 2007 - 18:48:59 GMT


I have a question about making n step ahead forecasts in cases where test and validation sets are availiable. For instance, I would like to make one step ahead forecasts on the WWWusage data so I hold out the last 10 observations as the validation set and fit an ARIMA model on the first 90 observations. I then use a for loop to sequentially add 9 of the holdout observations to make 1 step ahead forecasts for the last 10 periods (see example code). In cases where there are relatively few periods I want to forecast for this seems to work fine, however I am working with a rather large validation set and I need to make n step ahead forecasts for many periods and it takes a very long time. Is there a more efficient way to do this?

vset <- WWWusage[91:100]

pred <-c()
for (i in 0:9)

    { fit <-arima(WWWusage[1:(90+i)],c(3,1,0))

      p<- predict(fit,se.fit=F)
      pred <- c(pred, p)




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