simulate_mpp: Simulate a realization of a location dependent marked point...

In ldmppr: Estimate and Simulate from Location Dependent Marked Point Processes

Simulate a realization of a location dependent marked point process

Description

Simulate a realization of a location dependent marked point process

Usage

simulate_mpp(
  sc_params = NULL,
  t_min = 0,
  t_max = 1,
  anchor_point = NULL,
  raster_list = NULL,
  scaled_rasters = FALSE,
  mark_model = NULL,
  xy_bounds = NULL,
  include_comp_inds = FALSE,
  competition_radius = 15,
  correction = "none",
  thinning = TRUE
)

Arguments

sc_params	vector of parameter values corresponding to (alpha_1, beta_1, gamma_1, alpha_2, beta_2, alpha_3, beta_3, gamma_3).
t_min	minimum value for time.
t_max	maximum value for time.
anchor_point	vector of (x,y) coordinates of point to condition on.
raster_list	list of raster objects.
scaled_rasters	'TRUE' or 'FALSE' indicating whether the rasters have been scaled.
mark_model	a model object (typically from train_mark_model).
xy_bounds	a vector of domain bounds (2 for x, 2 for y).
include_comp_inds	'TRUE' or 'FALSE' indicating whether to generate and use competition indices as covariates.
competition_radius	distance for competition radius if include_comp_inds is 'TRUE'.
correction	type of correction to apply ("none" or "toroidal").
thinning	'TRUE' or 'FALSE' indicating whether to thin the realization.

Value

a list containing the marked point process realization and the data frame of the realization.

Examples

# Specify the generating parameters of the self-correcting process
generating_parameters <- c(2, 8, .02, 2.5, 3, 1, 2.5, .2)

# Specify an anchor point
M_n <- matrix(c(10, 14), ncol = 1)

# Load the raster files
raster_paths <- list.files(system.file("extdata", package = "ldmppr"),
  pattern = "\\.tif$", full.names = TRUE
)
raster_paths <- raster_paths[!grepl("_med\\.tif$", raster_paths)]
rasters <- lapply(raster_paths, terra::rast)

# Scale the rasters
scaled_raster_list <- scale_rasters(rasters)

# Load the example mark model
file_path <- system.file("extdata", "example_mark_model.rds", package = "ldmppr")
mark_model <- bundle::unbundle(readRDS(file_path))

# Simulate a realization
example_mpp <- simulate_mpp(
  sc_params = generating_parameters,
  t_min = 0,
  t_max = 1,
  anchor_point = M_n,
  raster_list = scaled_raster_list,
  scaled_rasters = TRUE,
  mark_model = mark_model,
  xy_bounds = c(0, 25, 0, 25),
  include_comp_inds = TRUE,
  competition_radius = 10,
  correction = "none",
  thinning = TRUE
)

# Plot the realization
plot_mpp(example_mpp$mpp, pattern_type = "simulated")

ldmppr documentation built on April 4, 2025, 12:45 a.m.