arameter Estimations of Hyperbolic and Normal Inverse Gaussian
Distributions
by Mounir Aout.
Abstract:
Generalized Hyperbolic distributions,
introduced by Barndorff-Nielsen in 1977, have become quite popular in
various areas of theoretical and applied statistics. These
distributions possess a number of attractive properties and they
allow representation of the skewness and their tails tend to be
heavier than those of the normal. In this paper we develop a
numerical algorithm for estimating the parameters of both
Hyperbolic (HYP) and Normal Inverse Gaussian (NIG) distributions via
Maximum Likelihood. This task relies on numerical methods for
solving systems of nonlinear equations. We also give two C programs, based
on GSL library
available under GPL license, for the estimation procedure.
Key Words:
Hyperbolic distributions, Normal Inverse Gaussian distributions,
maximum likelihood, C programs
Author:
Mounir Aout, m.aout@lisieux.iutcaen.unicaen.fr
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