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Publication
Bayesian inference for skew-symmetric distributions
Journal Contribution - Journal Article
Skew-symmetric distributions are a popular family of flexible distributions that conveniently model non-normal features such as skewness, kurtosis and multimodality. Unfortunately, their frequentist inference poses several difficulties, which may be adequately addressed by means of a Bayesian approach. This paper reviews the main prior distributions proposed for the parameters of skew-symmetric distributions, with special emphasis on the skew-normal and the skew-t distributions which are the most prominent skew-symmetric models. The paper focuses on the univariate case in the absence of covariates, but more general models are also discussed.
Journal: SYMMETRY-BASEL
ISSN: 2073-8994
Issue: 4
Volume: 12
Publication year:2020
Accessibility:Open