Geostatistical Modeling of Spatially Referenced Data
Assess Predictive Performance via Spatial Cross-Validation
Assess Simulations
Check MCMC Convergence for Spatial Random Effects
Extract Parameter Estimates from a "RiskMap" Model Fit
Compute Unique Coordinate Identifiers
Convex Hull of an sf Object
Create Grid of Points Within Shapefile
Fitting of decay-adjusted spatio-temporal (DAST) model
Summaries of the distances
Simulation from Generalized Linear Gaussian Process Models
Estimation of Generalized Linear Gaussian Process Models
Gaussian Process Model Specification
Laplace-sampling MCMC for Generalized Linear Gaussian Process Models
Matern Correlation Function
First Derivative with Respect to
Second Derivative with Respect to
Maximization of the Integrand for Generalized Linear Gaussian Process ...
Plot Calibration Curves (AnPIT / PIT) from Spatial Cross-Validation
Plot the estimated MDA impact function
Plotting the empirical variogram
Plot Spatial Scores for a Specific Model and Metric
Plot simulated surface data for a given simulation
Plot Method for RiskMap_pred_target_grid Objects
Plot Method for RiskMap_pred_target_shp Objects
Prediction of the random effects components and covariates effects ove...
Predictive Target Over a Regular Spatial Grid
Predictive Targets over a Shapefile (grid-aggregated)
Print Summary of RiskMap Model
Print Simulation Results
Print Summary of RiskMap Spatial Cross-Validation Scores
EPSG of the UTM Zone
Random Effect Model Specification
Empirical variogram
Set Control Parameters for Simulation
Summarize Model Fits
Summarize Simulation Results
Summarize Cross-Validation Scores for Spatial RiskMap Models
Simulate surface data based on a spatial model
Generate LaTeX Tables from RiskMap Model Fits and Validation
Update Predictors for a RiskMap Prediction Object
Geostatistical analysis of continuous and count data. Implements stationary Gaussian processes with Matérn correlation for spatial prediction, as described in Diggle and Giorgi (2019, ISBN: 978-1-138-06102-7).