covmmtmt#

Purpose#

Prints covariance matrix of parameters with labels.

Format#

a = covmmt(vout);

Parameters:: vout (structure) – a post-estimation instance of the varmamtOut.
Returns:: cov (scalar)

Example#

new;
cls;
library tsmt;

// Create file name with full path
fname = getGAUSSHome("pkgs/tsmt/examples/mink.csv");

// Load two variables from the dataset into matrix 'y'
y = loadd(fname, "LogMink + LogMusk");

// Difference the data
y = vmdiffmt(y, 1);

// Declare 'vout' to be a varmamtOut structure
struct varmamtOut vout;

// Estimate the parameters of the VAR(1) model
vout = varmaFit(y, 1);

// Print covariance matrix
print covmmt(vout);

The printed covariance matrix is:

Covariance Matrix:

            phi[1,1,1]  phi[1,1,2]  phi[1,2,1]  phi[1,2,2]     vc[1,1]     vc[2,1]     vc[2,2]

phi[1,1,1]     0.01557    -0.00504     0.00530    -0.00155     0.00001     0.00000    -0.00001
phi[1,1,2]    -0.00504     0.01124    -0.00193     0.00384     0.00000     0.00001     0.00000
phi[1,2,1]     0.00530    -0.00193     0.01571    -0.00511     0.00001     0.00000    -0.00001
phi[1,2,2]    -0.00155     0.00384    -0.00511     0.01129     0.00000     0.00001     0.00001
   vc[1,1]     0.00001     0.00000     0.00001     0.00000     0.00016     0.00005     0.00002
   vc[2,1]     0.00000     0.00001     0.00000     0.00001     0.00005     0.00009     0.00006
   vc[2,2]    -0.00001     0.00000    -0.00001     0.00001     0.00002     0.00006     0.00016

Library#

tsmt

Source#

autoregmt.src