buffer_polygon          Enlarge/Buffer a Polygon
clean_coordinates       Clean Coordinates of Presence/Absence Data
contBoyce               Continuous Boyce Index (CBI) with weighting
create_coords_layer     Create Geographic Coordinate Layers
cross_validate_model    Cross-validation for BART model
evaluation_metrics      Evaluation metrics for model predictions
extract_noNA_cov_values
                        Extract Non-NA Covariate Values
fit_bart_model          Fit a BART Model Using Environmental Covariate
                        Layers
generate_cv_folds       Generate cross-validation folds
generate_pa_buffer_out
                        Generate Pseudo-Absences Using Buffer-Out
                        Strategy
generate_pa_env_space_flexsdm
                        Generate Environmental-space Pseudo-Absences
                        via flexsdm (per temporal stratum)
generate_pa_random      Generate Random Pseudo-Absences
generate_pa_target_group
                        Generate Pseudo-Absences Using Target-Group
                        Background
generate_pseudo_absences
                        Generate Pseudo-Absence Points Using Different
                        Methods Based on Presence Points, Covariates,
                        and Study Area Polygon
glossa_analysis         Main Analysis Function for GLOSSA Package
invert_polygon          Invert a Polygon
layer_mask              Apply Polygon Mask to Raster Layers
pa_optimal_cutoff       Optimal Cutoff for Presence-Absence Prediction
plot_cv_folds_points    Plot cross-validation fold assignments
predict_bart            Make Predictions Using a BART Model
remove_duplicate_points
                        Remove Duplicated Points from a Dataframe
remove_points_polygon   Remove Points Inside or Outside a Polygon
response_curve_bart     Calculate Response Curve Using BART Model
run_glossa              Run GLOSSA Shiny App
variable_importance     Variable Importance in BART Model
