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On Bayesian Modelling of Fat Tails and Skewness
1996
Social Science Research Network
We consider a Bayesian analysis of linear regression models that can account for skewed error distributions with fat tails. The latter two features are often observed characteristics of empirical data sets, and we will formally incorporate them in the inferential process. A general procedure for introducing skewness into symmetric distributions is rst proposed. Even though this allows for a great deal of exibility in distributional shape, tail behaviour is not aected. In addition, the impact on
doi:10.2139/ssrn.821
fatcat:slglkyzmvfgyfdfh6v3jst3v5m