Suppose you have a matrix of time series, where each column is a time series.

Now, suppose you take second differences of this matrix, (so the data is stationary), using this code:

var_train_data <- diff(var_train, differences = 2)

and then you estimate this model:

var_1 <- VAR(y=var_train_data, lag=9, type="const")

Recall that this function VARcomes from vars package.

How can you plot the original data and the fitted(var_1) data? Is there a function to return the fitted data from the VAR to "level"?

I want to do this but with a VAR.

Thanks in advance!!

---

Here is the data:

> dput(var_train)
structure(c(8.59225428063812, 8.61632381521795, 8.48941975098913, 
8.42616336163893, 8.4656261753598, 8.49981580266834, 8.50658473928686, 
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