A new class of multivariate skew distributions with applications to bayesian regression models
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Abstract
Abstract Abstract: The authors develop a new class of distributions by introducing skewness in multivariate elliptically symmetric distributions. The class, which is obtained by using transformation and conditioning, contains many standard families including the multivariate skew‐normal and t distributions. The authors obtain analytical forms of the densities and study distributional properties. They give practical applications in Bayesian regression models and results on the existence of the posterior distributions and moments under improper priors for the regression coefficients. They illustrate their methods using practical examples.
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The record
- Venue
- Canadian Journal of Statistics
- Topic
- Statistical Distribution Estimation and Applications
- Field
- Mathematics
- Canadian institutions
- —
- Funders
- —
- Keywords
- Multivariate statisticsSkewnessBayesian linear regressionBayesian multivariate linear regressionPrior probabilityMathematicsSkewBayesian probabilitySkew normal distributionClass (philosophy)StatisticsTransformation (genetics)Regression analysisApplied mathematicsEconometricsBayesian inferenceComputer scienceArtificial intelligence
- Has abstract in OpenAlex
- yes