Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures

DOI10.1214/18-BJPS417zbMath1440.62267arXiv1509.00331MaRDI QIDQ2180257

Flávio B. Gonçalves, Victor Hugo Lachos, Marcos Oliveira Prates

Publication date: 13 May 2020

Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.00331

zbMATH Keywords

MCMCStudent-\(t\)penalised complexity priorsscale mixtures of normal

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03) Censored data models (62N01) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (3)

Bayesian linear regression models with flexible error distributions ⋮ Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures ⋮ A parametric regression framework for the skew sinh-arcsinh \(t\) distribution

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