| 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 |