# Estimate and Simulate from Location Dependent Marked Point Processes

## Documentation for package ‘ldmppr’ version 1.0.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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