Multivariate Analysis of Spatial Data Using a Unifying Spatial Fusion Framework
Municipality map for Canton of Zurich
Obtain fitted values of spatial fusion model
Fit a spatial fusion model using INLA
Fit a spatial fusion model using Stan
Fit a spatial fusion model
Prepare data structure for spatial fusion modelling
Simulate spatial data
Simulated geostatistical data
Simulated lattice data
Generate diagnostics plot for a fusion model
Simulated point pattern data
Obtain predictions for the latent processes of spatial fusion model
Multivariate Analysis of Spatial Data Using a Unifying Spatial Fusion ...
Obtain summary of parameter estimates for a spatial fusion model
Multivariate modelling of geostatistical (point), lattice (areal) and point pattern data in a unifying spatial fusion framework. Details are given in Wang and Furrer (2021) <doi:10.1016/j.csda.2021.107240>. Model inference is done using either 'Stan' <https://mc-stan.org/> or 'INLA' <https://www.r-inla.org/>.
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