11 citations · 11 across the 5 of their papers we have counts for
6 papers · 1 filter
A joint model for DHS and MICS surveys: Spatial modeling with anonymized locations
John Paige, Geir-Arne Fuglstad, Andrea Riebler
Anonymizing the GPS locations of observations can bias a spatial model's parameter estimates and attenuate spatial predictions when improperly accounted for, and is relevant in app…
Bayesian Multiresolution Modeling Of Georeferenced Data
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
Current implementations of multiresolution methods are limited in terms of possible types of responses and approaches to inference. We provide a multiresolution approach for spatia…
Design- and Model-Based Approaches to Small-Area Estimation in a Low and Middle Income Country Context: Comparisons and Recommendations
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
The need for rigorous and timely health and demographic summaries has provided the impetus for an explosion in geographic studies, with a common approach being the production of pi…
Intuitive joint priors for variance parameters
Geir-Arne Fuglstad, Ingeborg Gullikstad Hem, Alexander Knight +2
Variance parameters in additive models are typically assigned independent priors that do not account for model structure. We present a new framework for prior selection based on a…
Spatial modelling with R-INLA: A review
Haakon Bakka, Håvard Rue, Geir-Arne Fuglstad +5
Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realist…
Estimating Under Five Mortality in Space and Time in a Developing World Context
Jon Wakefield, Geir-Arne Fuglstad, Andrea Riebler +3
Accurate estimates of the under-5 mortality rate (U5MR) in a developing world context are a key barometer of the health of a nation. This paper describes new models to analyze surv…