63 citations · 227 across the 34 of their papers we have counts for
4 papers · 1 filter
Sensitivity analysis for Bayesian hierarchical models
Malgorzata Roos, Thiago G. Martins, Leonhard Held +1
Prior sensitivity examination plays an important role in applied Bayesian analyses. This is especially true for Bayesian hierarchical models, where interpretability of the paramete…
A skew Gaussian decomposable graphical model
Hamid Zareifard, Havard Rue, Majid Jafari Khaledi +1
This paper propose a novel decomposable graphical model to accommodate skew Gaussian graphical models. We encode conditional independence structure among the components of the mult…
Exploring a New Class of Non-stationary Spatial Gaussian Random Fields with Varying Local Anisotropy
Geir-Arne Fuglstad, Finn Lindgren, Daniel Simpson +1
Gaussian random fields (GRFs) constitute an important part of spatial modelling, but can be computationally infeasible for general covariance structures. An efficient approach is t…
Bayesian analysis of measurement error models using INLA
Stefanie Muff, Andrea Riebler, Havard Rue +2
To account for measurement error (ME) in explanatory variables, Bayesian approaches provide a flexible framework, as expert knowledge about unobserved covariates can be incorporate…