Length of time series to estimate VAR model
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I created a VAR(p) model with 12 time series (Y) highly correlated. p is detected iteratively in the interval [1,4] by comparing the aic index.
dim(Y) = (more than 350000,12).
Each time series has more than 350000 rows, there aren't nan elements.
I use the function "estimate" to find the parameters of the VAR(p) model: estimate(Mdl,Y).
This function uses all the elements of Y (except the p-rows for lag) or it uses a lower number of rows? Which is the optimum number of row to estimate the VAR(p) parameters? This is necessary to speed-up the solution.