VAR_pcovmat function

Calculate the dp-dimensional covariance matrix of p consecutive observations of a VAR process

VAR_pcovmat calculate the dp-dimensional covariance matrix of p consecutive observations of a VAR process with the algorithm proposed by McElroy (2017).

VAR_pcovmat(p, d, all_Am, Omega_m)

Arguments

• p: a positive integer specifying the autoregressive order
• d: the number of time series in the system, i.e., the dimension
• all_Am: [d, d, p] array containing the AR coefficient matrices
• Omega_m: the $(d\times d)$ positive definite error term covariance matrix

Returns

Returns the $(dp \times dp)$ covariance matrix.

Details

Most of the code in this function is adapted from the one provided in the supplementary material of McElroy (2017). Reproduced under GNU General Public License, Copyright (2015) Tucker McElroy.

References

• McElroy T. 2017. Computation of vector ARMA autocovariances. Statistics and Probability Letters, 124 , 92-96.