I'm using the `vars` package and want to predict some values from the calculated models:

```
# Get the model
x1 <- rnorm(15)
y1 <- x1 + rnorm(15)
trainFrame=data.frame(x1,y1);
model=VAR(trainFrame, p=3);
pr1=predict(model, trainFrame);
# Forecast values with new data
x2 <- rnorm(15)
y2 <- x2 + rnorm(15)
newFrame=data.frame(x2,y2);
pr2=predict(model, newFrame);

```

Comparing the two prediction vectors `pr1` and `pr2` shows that they are the same.
How can I get the actual forecast values and not again the forecasts from the training data?