ldmppr (version 1.1.0)

simulate_mpp: 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
)

Value

An object of class "ldmppr_sim".

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 (or 1x2 matrix) of (x,y) coordinates to condition on.

raster_list

list of raster objects.

scaled_rasters

`TRUE` or `FALSE` indicating whether the rasters have been scaled.

mark_model

a mark model (e.g., from train_mark_model()), or a path to a saved mark model.

xy_bounds

a vector of domain bounds (a_x, b_x, a_y, b_y).

include_comp_inds

`TRUE` or `FALSE` indicating whether to generate 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.

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 <- load_mark_model(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 and provide a summary
plot(example_mpp, pattern_type = "simulated")
summary(example_mpp)