Man pages for ldmppr
Estimate and Simulate from Location Dependent Marked Point Processes
| check_model_fit | Check the fit of estimated self-correcting model on the... |
| conditional_sum | calculates sum of values < t |
| conditional_sum_logical | calculates sum of values < t |
| C_theta2_i | calculates c_theta |
| dist_one_dim | calculates distance in one dim |
| estimate_parameters_sc | Estimate parameters of the self-correcting model using... |
| estimate_parameters_sc_parallel | Estimate parameters of the self-correcting model using... |
| extract_covars | Extract covariate values from a set of rasters |
| full_product | calculates full product for one grid point |
| full_sc_lhood | calculates full self-correcting log-likelihood |
| generate_mpp | Generate a marked process given locations and marks |
| interaction_st | calculates spatio-temporal interaction |
| ldmppr-package | ldmppr: Estimate and Simulate from Location Dependent Marked... |
| medium_example_data | Medium Example Data |
| part_1_1_full | calculates part 1-1 full |
| part_1_2_full | calculates part 1-2 full |
| part_1_3_full | calculates part 1-3 |
| part_1_4_full | calculates part 1-4 |
| part_1_full | calculates part 1 of the likelihood |
| part_2_full | calculates part 2 of the likelihood |
| pipe | Pipe operator |
| plot_mpp | Plot a marked point process |
| power_law_mapping | Gentle decay (power-law) mapping function from sizes to... |
| predict_marks | Predict values from the mark distribution |
| scale_rasters | Scale a set of rasters |
| sim_spatial_sc | Simulate the spatial component of the self-correcting model |
| sim_temporal_sc | Simulate the temporal component of the self-correcting model |
| simulate_mpp | Simulate a realization of a location dependent marked point... |
| simulate_sc | Simulate from the self-correcting model |
| small_example_data | Small Example Data |
| spat_interaction | calculates spatial interaction |
| temporal_sc | calculates temporal likelihood |
| toroidal_dist_matrix_optimized | Optimized function to compute toroidal distance matrix over a... |
| train_mark_model | Train a flexible model for the mark distribution |
| vec_dist | calculates euclidean distance |
| vec_to_mat_dist | calculates euclidean distance between a vector and a matrix |
