This is a wrapper for the `RFsimulate`

function in the `RandomFields`

package. The main addition is the `speedup`

argument which allows
for faster map generation. A `speedup`

of 1 is normal and will get
progressively faster as the number increases, at the expense of coarser
pixel resolution of the pattern generated.

```
gaussMap(
x,
scale = 10,
var = 1,
speedup = 1,
method = "RMexp",
alpha = 1,
inMemory = FALSE,
...
)
```

- x
A spatial object (e.g., a

`RasterLayer`

).- scale
The spatial scale in map units of the Gaussian pattern.

- var
Spatial variance.

- speedup
An numeric value indicating how much faster than 'normal' to generate maps. It may be necessary to give a value larger than 1 for large maps. Default is 1.

- method
The type of model used to produce the Gaussian pattern. Should be one of

`"RMgauss"`

(Gaussian covariance model),`"RMstable"`

(the stable powered exponential model), or the default,`"RMexp"`

(exponential covariance model).- alpha
A required parameter of the

`"RMstable"`

model. Should be in the interval`[0,2]`

to provide a valid covariance function. Default is 1.- inMemory
Should the RasterLayer be forced to be in memory? Default

`FALSE`

.- ...
Additional arguments to

`raster`

.

A raster map with same extent as `x`

, with a Gaussian random pattern.

`RFsimulate`

and `extent()`

```
if (FALSE) {
if (require(RandomFields)) {
library(raster)
nx <- ny <- 100L
r <- raster(nrows = ny, ncols = nx, xmn = -nx/2, xmx = nx/2, ymn = -ny/2, ymx = ny/2)
speedup <- max(1, nx/5e2)
map1 <- gaussMap(r, scale = 300, var = 0.03, speedup = speedup, inMemory = TRUE)
if (interactive()) Plot(map1)
# with non-default method
map1 <- gaussMap(r, scale = 300, var = 0.03, method = "RMgauss")
}
}
```