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Type: Artigo de periódico
Title: Multivariate Skew-Normal Generalized Hyperbolic distribution and its properties
Author: Vilca, F
Balakrishnan, N
Zeller, CB
Abstract: The Generalized Inverse Gaussian (GIG) distribution has found many interesting applications: see Jorgensen [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. (C) 2014 Elsevier Inc. All rights reserved.
Subject: Generalized inverse Gaussian distribution
Skew-normal distribution
Heavy-tailed distributions
Skewness and kurtosis
Normal inverse Gaussian distribution
Skew-Normal Generalized Hyperbolic distribution
Country: EUA
Editor: Elsevier Inc
Citation: Journal Of Multivariate Analysis. Elsevier Inc, v. 128, n. 73, n. 85, 2014.
Rights: fechado
Identifier DOI: 10.1016/j.jmva.2014.03.002
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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