VAR_pcovmat {sstvars}R Documentation

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

Description

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

Usage

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

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.

Value

Returns the (dp \times dp) covariance matrix.

References


[Package sstvars version 1.1.2 Index]