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Outlier models and prior distributions in Bayesian linear regression. (English) Zbl 0567.62022
Bayesian inference in regression models is considered using heavy-tailed error distributions to accommodate outliers. The particular class of distributions that can be constructed as scale mixtures of normal distributions are examined and use is made of them as both error models and prior distributions in Bayesian linear modelling, including simple regression and more complex hierarchical models with structured priors depending on unknown hyperprior parameters.

MSC:
62F15 Bayesian inference
62J05 Linear regression; mixed models
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