simLgcp(param, covariates=NULL, betas=NULL,
offset=NULL,
rasterTemplate=covariates[[1]], n=1, ...)
simPoissonPP(intensity)
range
and shape
(see Details), and optionally variance
(defaults to 1).
For Geometric Anisotropy add
anisoRatio
and either anisoAn
covariates
which are offsetsGaussRF
in the RandomFields package.events
element containing the event locations and a raster
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 = raster(nrows=15,ncols=20,xmn=0,xmx=10,ymn=0,ymx=7.5)
# some covariates, deliberately with a different resolution than myraster
covA = covB = myoffset = raster(extent(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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