9 papers
A parameterization of anisotropic Gaussian fields with penalized complexity priors
Liam Llamazares-Elias, Jonas Latz, Finn Lindgren
Gaussian random fields (GFs) are fundamental tools in spatial modeling and can be represented flexibly and efficiently as solutions to stochastic partial differential equations (SP…
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…
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…
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…
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…