simLgcp | R Documentation |
Give covariates and model parameters, simulates a log-Gaussian Cox process
simLgcp(param, covariates=NULL, betas=NULL,
offset=NULL,
rasterTemplate=covariates[[1]], n=1, ...)
simPoissonPP(intensity)
param |
A vector of named model parameters with, at a minimum names
|
covariates |
Either a raster stack or list of rasters and |
betas |
Coefficients for the covariates |
offset |
Vector of character strings corresponding to elements of |
rasterTemplate |
Raster on which the latent surface is simulated, defaults to the first covariate. |
n |
number of realisations to simulate |
... |
additional arguments, see \Sexpr[results=rd]{c( '\\\code{RFsimulate} in the \\\code{RandomFields} package', '\\\command{\\\\link[RandomFields]{RFsimulate}}' )[1+requireNamespace('RandomFields', quietly=TRUE)]}. |
intensity |
Raster of the intensity of a Poisson point process. |
A list with a events
element containing the event locations and a SpatRaster
element
containing a raster stack of the covariates, spatial random effect, and intensity.
mymodel = c(mean=-0.5, variance=1,
range=2, shape=2)
myraster = rast(nrows=15,ncols=20,xmin=0,xmax=10,ymin=0,ymax=7.5)
# some covariates, deliberately with a different resolution than myraster
covA = covB = myoffset = rast(ext(myraster), 10, 10)
values(covA) = as.vector(matrix(1:10, 10, 10))
values(covB) = as.vector(matrix(1:10, 10, 10, byrow=TRUE))
values(myoffset) = round(seq(-1, 1, len=ncell(myoffset)))
myCovariate = list(a=covA, b=covB, offsetFooBar = myoffset)
myLgcp=simLgcp(param=mymodel,
covariates=myCovariate,
betas=c(a=-0.1, b=0.25),
offset='offsetFooBar',
rasterTemplate=myraster)
plot(myLgcp$raster[["intensity"]], main="lgcp")
points(myLgcp$events)
myIntensity = exp(-1+0.2*myCovariate[["a"]])
myPoissonPP = simPoissonPP(myIntensity)[[1]]
plot(myIntensity, main="Poisson pp")
points(myPoissonPP)
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