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• W3014032959 startingPage "491" @default.
• W3014032959 abstract "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." @default.
• W3014032959 created "2020-04-03" @default.
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• W3014032959 date "2020-03-25" @default.
• W3014032959 modified "2023-10-18" @default.
• W3014032959 title "Bayesian Inference for Skew-Symmetric Distributions" @default.
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• W3014032959 doi "https://doi.org/10.3390/sym12040491" @default.
• W3014032959 hasPublicationYear "2020" @default.
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