Estimate and Simulate from Location Dependent Marked Point Processes
calculates c_theta
Check the fit of an estimated model using global envelope tests
calculates sum of values < t
calculates sum of values < t
calculates distance in one dim
Estimate point process parameters using log-likelihood maximization
Extract covariate values from a set of rasters
calculates full product for one grid point
calculates fast full self-correcting log-likelihood
calculates full self-correcting log-likelihood
Generate a marked process given locations and marks
calculates spatio-temporal interaction
Fitted point-process model object
Mark model object
Model fit diagnostic object
Simulated marked point process object
Internal helpers (not part of the public API)
ldmppr: Estimate and Simulate from Location Dependent Marked Point Pro...
calculates part 1-1 full
calculates part 1-2 full
calculates part 1-3
calculates part 1-4
calculates part 1 of the likelihood
calculates part 2 of the likelihood
Pipe operator
Plot a marked point process
Gentle decay (power-law) mapping function from sizes to arrival times
Predict values from the mark distribution
Scale a set of rasters
Simulate the spatial component of the self-correcting model
Simulate the temporal component of the self-correcting model
Simulate a realization of a location dependent marked point process
Simulate from the self-correcting model
calculates spatial interaction
calculates temporal likelihood
Optimized function to compute toroidal distance matrix over a rectangu...
Train a flexible model for the mark distribution
calculates euclidean distance
calculates euclidean distance between a vector and a matrix
A suite of tools for estimating, assessing model fit, simulating from, and visualizing location dependent marked point processes characterized by regularity in the pattern. You provide a reference marked point process, a set of raster images containing location specific covariates, and select the estimation algorithm and type of mark model. 'ldmppr' estimates the process and mark models and allows you to check the appropriateness of the model using a variety of diagnostic tools. Once a satisfactory model fit is obtained, you can simulate from the model and visualize the results. Documentation for the package 'ldmppr' is available in the form of a vignette.