92 citations · 232 across the 37 of their papers we have counts for
5 papers · 1 filter
Influence of river incision on landslides triggered in Nepal by the Gorkha earthquake: Results from a pixel-based susceptibility model using inlabru
Man Ho Suen, Mark Naylor, Simon Mudd +1
This study presents a comprehensive framework for modelling earthquake-induced landslides (EQILs) through a channel-based analysis of landslide centroid distributions. A key innova…
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…
Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data
Man Ho Suen, Mark Naylor, Finn Lindgren
Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that…