Robustifying Bayesian Hierarchical Models Using Intuitive Prior Elicitation
Doctoral thesis
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https://hdl.handle.net/11250/2759141Utgivelsesdato
2021Metadata
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Paper 1: Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea Ingeborg. Intuitive Joint Priors for Variance Parameters. Bayesian Analysis 2020 ;Volum 15.(4) s. 1109-1137 https://doi.org/10.1214/19-BA1185 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) (CC BY 4.0)Paper 2: Hem, Ingeborg Gullikstad; Selle, Maria; Gorjanc, Gregor; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge. Genetics 2021 ;Volum 217.(3) https://doi.org/10.1093/genetics/iyab002 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) (CC BY 4.0)
Paper 3: Hem, Ingeborg Gullikstad; Fuglstad, Geir-Arne; Riebler,Andrea makemyprior: Intuitive construction of joint priors for variance parameters in R. https://arxiv.org/abs/2105.09712