Description Usage Arguments Value Author(s) See Also Examples
Generate one (or several) realisation(s) of the Poisson cluster process in a region S x T.
1 2 3 |
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 |
nparents |
number of parents. If NULL, |
npoints |
number of points to simulate. If NULL (default), the
number of points is from a Poisson distribution with mean the double integral
of the intensity over |
lambda |
intensity of the parent process. Can be either a numeric
value, a function, or a 3d-array (see |
mc |
average number of children per parent. It is used when
|
nsim |
number of simulations to generate. |
cluster |
distribution of children: “uniform”, “normal” and “exponential” are currently implemented. Either a single value if the distribution in space and time is the same, or a vector of length 2, giving first the spatial distribution of children and then the temporal distribution. |
dispersion |
scale parameter. It equals twice the standard deviation of location of children relative to their parent for a normal distribution of children; the mean for an exponential distribution and half range for an uniform distribution. |
infectious |
If TRUE, offspring's times are always greater than parent's time). |
edge |
specify the edge correction to use "larger.region" or "without". |
larger.region |
By default, the larger spatial region is the convex hull
of |
tronc |
parameter of the truncated exponential distribution for the distribution of children. |
... |
additional parameters of the intensity of the parent process. |
A list containing:
xyt |
matrix (or list of matrices if |
s.region, t.region |
parameters passed in argument. |
Edith Gabriel <edith.gabriel@univ-avignon.fr>, 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 | # homogeneous Poisson distribution of parents
data(northcumbria)
pcp1 <- rpcp(nparents=50, npoints=500, s.region=northcumbria, t.region=c(1,365),
cluster=c("normal","exponential"), maxrad=c(5000,5))
## Not run:
animation(pcp1$xyt, s.region=pcp1$s.region, t.region=pcp1$t.region,runtime=5)
## End(Not run)
# inhomogeneous Poisson distribution of parents
lbda <- function(x,y,t,a){a*exp(-4*y) * exp(-2*t)}
pcp2 <- rpcp(nparents=50, npoints=500, cluster="normal", lambda=lbda,
a=4000/((1-exp(-4))*(1-exp(-2))))
## Not run:
stan(pcp2$xyt)
## End(Not run)
|
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