boundary_null_distrib {BoundaryStats} | R Documentation |
Null distribution for overlap statistics
Description
Creates custom probability distributions for two boundary statistics (number of subgraphs and length of the longest subgraph). Given a SpatRaster object, simulates n iterations of random raster surfaces from a neutral model.
Usage
boundary_null_distrib(
x,
convert = FALSE,
cat = FALSE,
threshold = 0.2,
n_iterations = 10,
model = "random",
p = 0.5,
progress = TRUE
)
Arguments
x |
A SpatRaster object. |
convert |
TRUE if x contains numeric trait data that needs to be converted to boundary intensities. default = FALSE. |
cat |
TRUE if the input SpatRaster contains a categorical variable. default = FALSE. |
threshold |
A value between 0 and 1. The proportion of cells to keep as boundary elements. default = 0.2. |
n_iterations |
An integer indicating the number of iterations for the function. A value of 100 or 1000 is recommended to produce sufficient resolution for downstream statistical tests. default = 10. |
model |
Neutral model to use. Options: 'random' (stochastic), 'gaussian' (Gaussian random field), and 'random_cluster' (modified random clusters method) |
p |
If using modified random clusters, proportion of cells to be marked in percolated raster.Higher values of p produce larger clusters. Default: p = 0.5 |
progress |
If progress = TRUE (default) a progress bar will be displayed. |
Value
A list of two probability distribution functions for boundary statistics.
Author(s)
Amy Luo
References
Saura, S. & Martínez-Millán, J. (2000). Landscape patterns simulation with a modified random clusters method. Landscape Ecology, 15:661-678.
Examples
data(T.cristatus)
T.cristatus <- terra::rast(T.cristatus_matrix, crs = T.cristatus_crs)
terra::ext(T.cristatus) <- T.cristatus_ext
T.crist_bound_null <- boundary_null_distrib(T.cristatus, cat = TRUE, n_iterations = 100,
model = 'random_cluster')