1.7k citations · 4.6k across the 36 of their papers we have counts for
3 papers · 2 filters
Spatial Modeling, with Application to Complex Survey Data: Discussion of "Model-based Geostatistics for Prevalence Mapping in Low-Resource Settings", by Diggle and Giorgi
Jon Wakefield, Daniel Simpson, Jessica Godwin
Prevalence mapping in low resource settings is an increasingly important endeavor to guide policy making and to spatially and temporally characterize the burden of disease. We will…
Bayesian Computing with INLA: A Review
Håvard Rue, Andrea Riebler, Sigrunn H. Sørbye +3
The key operation in Bayesian inference, is to compute high-dimensional integrals. An old approximate technique is the Laplace method or approximation, which dates back to Pierre-…
An intuitive Bayesian spatial model for disease mapping that accounts for scaling
Andrea Riebler, Sigrunn H. Sørbye, Daniel Simpson +1
In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulat…