How is the covariance matrix calculated in the MAXLIK?

Hi I have a question about how the covariance is estimated in MAXLIK. I have calculated the hessian by :

vread(_max_Diagnostic,"hessian");

which gives me:

0.098854902 -0.044789408 0.21265749 -0.098746774
-0.044789408 0.097216091 -0.097149608 0.21118073
0.21265749 -0.097149608 0.66755658 -0.33440959
-0.098746774 0.21118073 -0.33440959 0.66921942

The inverse of this matrix is:

45.059278 24.224743 -15.109826 -8.5460929
24.224743 45.880519 -8.6733621 -15.237785
-15.109826 -8.6733621 7.0742131 4.0424484
-8.5460929 -15.237785 4.0424484 7.0617510

However when I use cov, I get:

 0.057190334  0.030671550 -0.018652539 -0.010151653  . . . . .
 0.030671550  0.057763764 -0.010134082 -0.019056447  . . . . .
-0.018652539 -0.010134082  0.0081342988 0.0043459482 . . . . .
-0.010151653 -0.019056447  0.0043459482 0.0083873686 . . . . .
            .           .            .             . . . . . .
            .           .            .             . . . . . .
            .           .            .             . . . . . .
            .           .            .             . . . . . .
            .           .            .             . . . . . .

which is different from the inverse of the Hessian matrix.

I have 1000 observations, _max_CovPar is set to 1, and the gradient is calculated numerically. This is the gradient:

-0.00033315205
-0.00010445805
-0.00079539564
-0.00014439259


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