Description Usage Arguments Value Author(s) See Also Examples
Generate one (or several) realisation(s) of the (homogeneous or inhomogeneous) Poisson process in a region S x T.
1 2 |
lambda |
Spatio-temporal intensity of the Poisson process.
If |
s.region |
two-column matrix specifying polygonal region containing
all data locations.
If |
t.region |
vector containing the minimum and maximum values of
the time interval.
If |
replace |
logical allowing times repeat. |
npoints |
number of points to simulate. If |
discrete.time |
if TRUE, times belong to N, otherwise belong to R^+. |
nsim |
number of simulations to generate. Default is 1. |
nx,ny,nt |
define the size of the 3-D grid on which the intensity is evaluated. |
lmax |
upper bound for the value of lambda(x,y,t), if
|
... |
additional parameters if |
A list containing:
xyt |
matrix (or list of matrices if |
t.index |
vector of times index. |
Lambda |
nx x ny x nt array of the intensity surface at each time. |
s.region, t.region, lambda |
parameters passed in argument. |
Edith Gabriel <edith.gabriel@univ-avignon.fr> and Peter J Diggle.
plot.stpp
, animation
and stan
for plotting space-time point patterns.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | # Homogeneous Poisson process
# ---------------------------
hpp1 <- rpp(lambda=200,replace=FALSE)
## Not run: stan(hpp1$xyt)
# fixed number of points, discrete time, with time repeat.
data(northcumbria)
hpp2 = rpp(npoints=500, s.region=northcumbria, t.region=c(1,1000), discrete.time=TRUE)
## Not run:
polymap(northcumbria)
animation(hpp2$xyt, s.region=hpp2$s.region, t.region=hpp2$t.region, runtime=10, add=TRUE)
## End(Not run)
# Inhomogeneous Poisson process
# -----------------------------
# intensity defined by a function
lbda1 = function(x,y,t,a){a*exp(-4*y) * exp(-2*t)}
ipp1 = rpp(lambda=lbda1, npoints=400, a=3200/((1-exp(-4))*(1-exp(-2))))
## Not run: stan(ipp1$xyt)
# intensity defined by a matrix
data(fmd)
data(northcumbria)
h = mse2d(as.points(fmd[,1:2]), northcumbria, nsmse=30, range=3000)
h = h$h[which.min(h$mse)]
Ls = kernel2d(as.points(fmd[,1:2]), northcumbria, h, nx=100, ny=100)
Lt = dim(fmd)[1]*density(fmd[,3], n=200)$y
Lst=array(0,dim=c(100,100,200))
for(k in 1:200) Lst[,,k] <- Ls$z*Lt[k]/dim(fmd)[1]
ipp2 = rpp(lambda=Lst, s.region=northcumbria, t.region=c(1,200), discrete.time=TRUE)
## Not run:
par(mfrow=c(1,1))
image(Ls$x, Ls$y, Ls$z, col=grey((1000:1)/1000)); polygon(northcumbria)
animation(ipp2$xyt, add=TRUE, cex=0.5, runtime=15)
## End(Not run)
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