check_model_fit         Check the fit of estimated self-correcting
                        model on the reference point pattern dataset
estimate_parameters_sc
                        Estimate parameters of the self-correcting
                        model using log-likelihood optimization
estimate_parameters_sc_parallel
                        Estimate parameters of the self-correcting
                        model using log-likelihood maximization in
                        parallel
extract_covars          Extract covariate values from a set of rasters
generate_mpp            Generate a marked process given locations and
                        marks
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
train_mark_model        Train a flexible model for the mark
                        distribution
