92 citations · 232 across the 37 of their papers we have counts for
27 papers · 1 filter
Cross Validation for the log Gaussian Cox Process
Hans Montcho, Håvard Rue, Finn Lindgren +4
The log Gaussian Cox Process (LGCP) is one of the most widely used models for the analysis of spatial point patterns. Although Bayesian methods and software for fitting LGCPs are n…
Spatially continuous modelling of aggregated outcome data
Stephen Jun Villejo, Peter Diggle, Finn Lindgren +5
This work develops a block aggregation approach to spatial estimation and prediction when the response is observed at a coarse spatial scale, for example as counts of events in adm…
Areal Disaggregation: A Small Area Estimation Perspective
Yunhan Wu, Finn Lindgren, Heidi A. Hanson
Producing reliable estimates of health and demographic indicators at fine areal scales is crucial for examining heterogeneity and supporting localized health policy. However, many…
Joint Modelling of Line and Point Data on Metric Graphs
Karina Lilleborge, Sara Martino, Geir-Arne Fuglstad +2
Metric graphs are useful tools for describing spatial domains like road and river networks, where spatial dependence act along the network. We take advantage of recent developments…
Bayesian inference for case-control point pattern data in spatial epidemiology with the \texttt{inlabru} R package
Francisco Palmí-Perales, Finn Lindgren, Virgilio Gómez-Rubio
The analysis of case-control point pattern data is an important problem in spatial epidemiology. The spatial variation of cases if often compared to that of a set of controls to as…
Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration
Stephen Jun Villejo, Sara Martino, Janine Illian +2
This work tackles the problem of uncertainty propagation in two-stage Bayesian models, with a focus on spatial applications. A two-stage modeling framework has the advantage of bei…