  The accurate computation of the covariance matrix of fitted model parameters
is a somewhat neglected task in Statistics. Algorithms are given for computing
accurate covariance matrices derived from computing the Hessian matrix by
numerical differentiation, and also for the covariance matrix of the posterior
distribution of model parameters. Evaluations on two datasets where the Hessian
could be computed analytically show that the numerical differentiation
algorithm is very accurate.
