eng
Science and Education Publishing
American Journal of Applied Mathematics and Statistics
2328-7292
2019-12-10
7
6
224
230
10.12691/ajams-7-6-4
AJAMS2019764
article
On Extended Normal Inverse Gaussian Distribution: Theory, Methodology, Properties and Applications
Bachioua Lahcene
drbachioua@gmail.com
1
Department of Basic Sciences, Prep. Year, P.O. Box 2440, University of Hail, Hail, Saudi Arabia
In this article, the Normal Inverse Gaussian Distribution model (NIGDM) is extended to a new Extended Normal Inverse Gaussian Distribution (ENIGDM) and its derivate models find many applications. The author proposes a new model ENIGDM, which generalizes the models of normal inverse Gaussian distribution. This class of ENIGDM is to approximate an unknown risk-neutral density. The paper discusses different properties of the ENIGDM. In particular, the applicability of this new general model with five parameters is well justified by more results which represent mixtures of inverse Gaussian distributions. Then a discussion is begun of the potential of the normal inverse Gaussian distribution and Lévy’s process for modeling and analyzing statistical data, with a particular reference to extensive sets of observations and applications in wide varieties.
http://pubs.sciepub.com/ajams/7/6/4/ajams-7-6-4.pdf
Normal-Inverse Gaussian distribution
generating and Quantile functions
goodness-of-fit
characteristics function
survival function
mixtures