Multivariate Skew-Normal Generalized Hyperbolic distribution and its properties
Filidor Vilca,
N. Balakrishnan and
Camila Borelli Zeller
Journal of Multivariate Analysis, 2014, vol. 128, issue C, 73-85
Abstract:
The Generalized Inverse Gaussian (GIG) distribution has found many interesting applications; see Jørgensen [24]. This rich family includes some well-known distributions, such as the inverse Gaussian, gamma and exponential, as special cases. These distributions have been used as the mixing density for building some heavy-tailed multivariate distributions including the normal inverse Gaussian, Student-t and Laplace distributions. In this paper, we use the GIG distribution in the context of the scale-mixture of skew-normal distributions, deriving a new family of distributions called Skew-Normal Generalized Hyperbolic distributions. This new flexible family of distributions possesses skewness with heavy-tails, and generalizes the symmetric normal inverse Gaussian and symmetric generalized hyperbolic distributions.
Keywords: Generalized inverse Gaussian distribution; Skew-normal distribution; Heavy-tailed distributions; Skewness and kurtosis; Normal inverse Gaussian distribution; Skew-Normal Generalized Hyperbolic distribution; Mixtures (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (8)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:128:y:2014:i:c:p:73-85
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DOI: 10.1016/j.jmva.2014.03.002
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