Riebler 2016 - BYM2 Intuitive Spatial Model

Routing Summary

Full capture of Riebler, Sorbye, Simpson and Rue (2016), An intuitive Bayesian spatial model for disease mapping that accounts for scaling (SMMR; arXiv:1601.01180): the BYM2 parameterisation, graph-dependent scaling, PC priors for , simulation and Sardinia IDDM application.

Concept Map

ConceptNoteTypeDepends OnKey Result
Besag/BYM/Leroux/DeanRiebler 2016 - Classical Disease Mapping Models Besag BYM Leroux DeandefinitionnoneLeroux cannot be scaled
Scaling, BYM2Riebler 2016 - Scaling and the BYM2 Constructiontheoremclassical models varies 0.29 to 4.78 across maps
PC priorsRiebler 2016 - Penalised Complexity Priors for BYM2theoremBYM2; type-2 Gumbel
Simulation, SardiniaRiebler 2016 - Simulation Study and Sardinia IDDM ApplicationexamplePC priorsshrinks to both base models

Notes

Sources

Riebler 2016 - BYM2 An Intuitive Bayesian Spatial Model for Disease Mapping

See Also

Spatial Models - BYM | Simpson 2016 - Going Off Grid - Overview