check_model_fit         Check the fit of an estimated model using
                        global envelope tests
estimate_process_parameters
                        Estimate point process parameters using
                        log-likelihood maximization
extract_covars          Extract covariate values from a set of rasters
generate_mpp            Generate a marked process given locations and
                        marks
ldmppr_budgets          Create an optimization budget specification for
                        estimate_process_parameters()
ldmppr_budgets-class    Optimization budget specification object
ldmppr_fit              Fitted point-process model object
ldmppr_grids            Create a grid schedule for
                        estimate_process_parameters()
ldmppr_grids-class      Grid schedule object
ldmppr_mark_model       Mark model object
ldmppr_model_check      Model fit diagnostic object
ldmppr_sim              Simulated marked point process object
medium_example_data     Medium Example Data
plot_mpp                Plot a marked point process
power_law_mapping       Gentle decay (power-law) mapping function from
                        sizes to arrival times
predict_marks           Predict values from the mark distribution
scale_rasters           Scale a set of rasters
simulate_mpp            Simulate a realization of a location dependent
                        marked point process
simulate_sc             Simulate from the self-correcting model
small_example_data      Small Example Data
thin_st_fast            calculates acceptance for thinning mechanism
                        during simulation
train_mark_model        Train a flexible model for the mark
                        distribution
