Hello,
I don't think is possible to do multiple steps ahead prediction using timedelaynets, recall that a timedelaynet it used for a time series like: y(t+1)=f(x(t),x(t-1),...,x(t-d)), therefore, to do predictions you will need the next values of x, that we usually don't have.
You can do multiple steps ahead predictions with narnets, since they model: y(t+1)=f(y(t),....,y(t-d)), therefore you use the same output of the net to do the predictions.
You can do multiple steps ahead predictions with narxnet, since they model: y(t+1)=f(x(t),....,x(t-dx),y(t),....y(t-dy)), as long as you have the next values of x.
However, recall that the time delay has the form: d1:d2, where d2 is the time delay, but d1 is usually 1, so you are doing 1 step ahead prediction. So it you use d1>1, you'll doing multistep ahead prediction, but nothing ensures it will work ok.
