Numerical optimizers can be used to fit univariate Generalized Hyperbolic distributions to data by means of
maximum likelihood estimation. Multivariate Generalized Hyperbolic distributions can be fitted with expectation maximization (EM) type algorithms (see Dempster et al. (1977) and Meng and Rubin (1993)).