A multivariate skew-normal-Tukey-h distribution
Sagnik Mondal and
Marc G. Genton
Journal of Multivariate Analysis, 2024, vol. 200, issue C
Abstract:
We introduce a new family of multivariate distributions by taking the component-wise Tukey-h transformation of a random vector following a skew-normal distribution with an alternative parameterization. The proposed distribution is named the skew-normal-Tukey-h distribution and is an extension of the skew-normal distribution for handling heavy-tailed data. We compare this proposed distribution to the skew-t distribution, which is another extension of the skew-normal distribution for modeling tail-thickness, and demonstrate that when there are substantial differences in marginal kurtosis, the proposed distribution is more appropriate. Moreover, we derive many appealing stochastic properties of the proposed distribution and provide a methodology for the estimation of the parameters that can be applied to large dimensions. Using simulations, as well as a wine and a wind speed data application, we illustrate how to draw inferences based on the multivariate skew-normal-Tukey-h distribution.
Keywords: Heavy-tails; Lambert’s-W; Non-gaussian distribution; Skew-normal; Skew-t; Tukey-h (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:200:y:2024:i:c:s0047259x23001069
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DOI: 10.1016/j.jmva.2023.105260
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