How to compute Fisher information and hessian matrix for multiple linear regression

Hi gyes

please help me how to calculate the Fisher information and Hessian matrix for the following multiple linear regression:

Y=XB+U

where :

Y=[2;4;3;2;1;5]

x=[1 1 1 1 1 1 ; 2 4 3 2 5 4; 2 4 5 6 3 2]

B=[2;6;3]

U is random error

[J. Alex Lee]

not sure what fisher information is, but the hessian matrix is related to the second partial derivatives of the underlying model (in this case linear), so wouldn't it be zeros?