# nlm_randomcluster

##### nlm_randomcluster

Simulates a random cluster nearest-neighbour neutral landscape.

##### Usage

```
nlm_randomcluster(ncol, nrow, resolution = 1, p, ai = c(0.5, 0.5),
neighbourhood = 4, rescale = TRUE)
```

##### Arguments

- ncol
[

`integer(1)`

] Number of columns forming the raster.- nrow
[

`integer(1)`

] Number of rows forming the raster.- resolution
[

`numerical(1)`

] Resolution of the raster.- p
[

`numerical(1)`

] Defines the proportion of elements randomly selected to form clusters.- ai
Vector with the cluster type distribution (percentages of occupancy). This directly controls the number of types via the given length.

- neighbourhood
[

`numerical(1)`

] Clusters are defined using a set of neighbourhood structures, 4 (Rook's or von Neumann neighbourhood) (default), 8 (Queen's or Moore neighbourhood).- rescale
[

`logical(1)`

] If`TRUE`

(default), the values are rescaled between 0-1.

##### Details

This is a direct implementation of steps A - D of the modified random clusters algorithm by Saura & Mart<U+00ED>nez-Mill<U+00E1>n (2000), which creates naturalistic patchy patterns.

##### Value

Raster with random values ranging from 0-1.

##### References

Saura, S. & Mart<U+00ED>nez-Mill<U+00E1>n, J. (2000) Landscape patterns simulation with a
modified random clusters method. *Landscape Ecology*, 15, 661 <U+2013> 678.

##### Examples

```
# NOT RUN {
# simulate random clustering
random_cluster <- nlm_randomcluster(ncol = 30, nrow = 30,
p = 0.4,
ai = c(0.25, 0.25, 0.5))
# }
# NOT RUN {
# visualize the NLM
landscapetools::show_landscape(random_cluster)
# }
# NOT RUN {
# }
```

*Documentation reproduced from package NLMR, version 0.4.2, License: GPL-3*