assign_features_to_polygons
                        Assign features to polygons and attach a
                        polygon ID
build_tessellation      Build a tessellation (Voronoi, Delaunay
                        triangles, hex grid, or square grid)
clear_fitted_cache      Clear cached fitted values for a Bayesian
                        spatial model
clear_grid_cache        Clear the in-session grid cache
clip_target_for         Build a polygonal clip target from points
                        and/or a boundary
coef.bayesian_fit       Extract Bayesian model fixed-effect summaries
coef.gwr_fit            Extract GWR local coefficients
coerce_to_points        Coerce arbitrary geometries to representative
                        points
compare_models          Side-by-side comparison of fitted spatial
                        models
compare_models_cv       Cross-validated comparison of spatial models
create_grid_polygons    Create square or hexagonal grid polygons over a
                        boundary
create_grid_polygons_cached
                        Create and cache grid polygons over a boundary
create_voronoi_polygons
                        Create Voronoi polygons from points with robust
                        CRS and optional clipping
cv_bayes                K-fold cross-validation for the Bayesian
                        spatial model
cv_gwr                  K-fold cross-validation for GWR
cv_spatial              Model-agnostic spatial cross-validation
determine_optimal_levels
                        Determine an optimal number of spatial levels
                        via an elbow heuristic
ensure_projected        Ensure an object has a projected CRS (with
                        sensible defaults)
ensure_stable_poly_id   Create deterministic, stable polygon IDs based
                        on spatial sort keys
estimate_sac_range      Estimate the spatial autocorrelation range from
                        data
evaluate_insample       Compute in-sample (or out-of-sample) metrics
                        for fitted spatial models
evaluate_models         Evaluate spatial models (legacy interface)
evaluate_models_cv      Cross-validated comparison with optional
                        tessellation (legacy interface)
fit_bayesian_spatial_model
                        Fit a Bayesian spatial regression with a 2D
                        Gaussian Process (via brms)
fit_gwr_model           Fit a Geographically Weighted Regression (GWR)
                        via GWmodel
get_voronoi_seeds       Generate seed points for Voronoi tessellation
gp_lengthscale_bounds   Heuristic length-scale bounds for a
                        squared-exponential GP
harmonize_crs           Harmonize CRS between two spatial objects
make_folds              Create spatial cross-validation folds
model_metrics           Compute goodness-of-fit metrics for a spatial
                        model
new_spatial_fit         Build a spatial_fit S3 object
plot_tessellation_map   Plot a tessellation map with optional boundary,
                        seeds, and features
predict.bayesian_fit    Predict from a Bayesian spatial GP model
predict.gwr_fit         Predict from a GWR spatial model
prep_model_data         Prepare and sanitize an sf dataset for spatial
                        modeling
residual_morans_i       Compute Moran's I on the residuals of a fitted
                        spatial model
summarize_by_cell       Summarize features by polygon/cell ID
voronoi_seeds_kmeans    K-means seed generation from point coordinates
voronoi_seeds_random    Random seed generation within a polygonal
                        boundary
