sthpcpp | R Documentation |
Generate a realisation of the hot-spots cluster process in a region S\times T
.
sthpcpp(lambp, r, mu, s.region, t.region)
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 |
lambp |
Intensity of the Poisson process of cluster centres. A single positive number, a function, or a pixel image. |
r |
Radius parameter of the clusters. |
mu |
Average number of daughter per parent (a single positive number) or reference intensity for the cluster points (a function or a pixel image). |
This function generates a realisation of spatio-temporal cluster process, which can be considered as generalisation of the classical Matern cluster process, inside the spatio-temporal window.
Consider a Poisson point process in the plane with intensity \lambda_{p}
as cluster centres for all times 'parent', as well as a infinite cylinder of radius R
around of each Poisson point, orthogonal to the plane. The scatter uniformly in all cylinders of all points which are of the form (x,y,z)
, the number of points in each cluster being random with a Poisson (\mu
) distribution. The resulting point pattern is a spatio-temporal cluster point process with t=z
. This point process has intensity \lambda_{p}\times\mu
.
The simulated spatio-temporal point pattern.
Francisco J. Rodriguez Cortes <frrodriguezc@unal.edu.co>
Baddeley, A., Rubak, E., Turner, R. (2015). Spatial Point Patterns: Methodology and Applications with R. CRC Press, Boca Raton.
Chiu, S. N., Stoyan, D., Kendall, W. S., and Mecke, J. (2013). Stochastic Geometry and its Applications. John Wiley & Sons.
Gabriel, E., Rowlingson, B., Diggle P J. (2013) stpp
: an R package for plotting, simulating and analyzing Spatio-Temporal Point Patterns. Journal of Statistical Software 53, 1-29.
Illian, J B., Penttinen, A., Stoyan, H. and Stoyan, D. (2008). Statistical Analysis and Modelling of Spatial Point Patterns. John Wiley and Sons, London.
Stoyan, D., Rodriguez-Cortes, F. J., Mateu, J., and Gille, W. (2017). Mark variograms for spatio-temporal point processes. Spatial Statistics. 20, 125-147.
# First example
X <- sthpcpp(lambp=20, r=0.05, mu=100)
plot(X$xyt)
# Spatio-temporal 3D scatter plot
par(mfrow=c(1,1))
plot(X$xyt,type="scatter")
## Spatio-temporal hot-spots cluster point process model
data(northcumbria)
Northcumbria <- northcumbria/1000
Xo <- sthpcpp(lambp=0.0035, r=5, mu=200,
s.region=Northcumbria, t.region=c(28,198))
plot(Xo$xyt,s.region=Northcumbria)
# Spatio-temporal 3D scatter plot
par(mfrow=c(1,1))
plot(Xo$xyt,type="scatter",style="elegant",theta=45,phi=30,cex=0.05,
ticktype="detailed",col="black")
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