simulate_data: Simulate data

In prioritizr: Systematic Conservation Prioritization in R

Simulate data

Description

Simulate spatially auto-correlated data using Gaussian random fields.

Usage

simulate_data(x, n, scale, intensity, sd, transform)

## S3 method for class 'Raster'
simulate_data(
  x,
  n = 1,
  scale = 0.5,
  intensity = 0,
  sd = 1,
  transform = identity
)

## S3 method for class 'SpatRaster'
simulate_data(
  x,
  n = 1,
  scale = 0.5,
  intensity = 0,
  sd = 1,
  transform = identity
)

Arguments

x	terra::rast() object to use as a template.
n	integer number of layers to simulate. Defaults to 1.
scale	numeric parameter to control level of spatial auto-correlation in the simulated data. Defaults to 0.5.
intensity	numeric average value of simulated data. Defaults to 0.
sd	numeric standard deviation of simulated data. Defaults to 1.
transform	function transform values output from the simulation. Defaults to the identity() function such that values remain the same following transformation.

Value

A terra::rast() object.

See Also

Other simulations: simulate_cost(), simulate_species()

Examples

## Not run: 
# create raster
r <- terra::rast(
  ncols = 10, nrows = 10, xmin = 0, xmax = 1, ymin = 0, ymax = 1, vals = 1
)

# simulate data using a Gaussian field
x <- simulate_data(r, n = 1, scale = 0.2)

# plot simulated data
plot(x, main = "simulated data", axes = FALSE)

## End(Not run)

prioritizr documentation built on Aug. 9, 2023, 1:06 a.m.