rpoispp

0th

Percentile

Generate Poisson Point Pattern

Generate a random point pattern using the (homogeneous or inhomogeneous) Poisson process.

Keywords
spatial
Usage
rpoispp(lambda, max, win)
Arguments
lambda
Intensity of the Poisson process. Either a single positive number, or a function(x,y).
max
An upper bound for the value of lambda(x,y), if lambda is a function.
win
Window in which to simulate the pattern. An object of class "owin" or something acceptable to as.owin.
Details

If lambda is a single number, then this algorithm generates a realisation of the uniform Poisson process inside the window win with intensity lambda (points per unit area). If lambda is a function, then this algorithm generates a realisation of the inhomogeneous Poisson process with intensity function lambda(x,y) at spatial location (x,y). The function lambda must work correctly with vectors x and y. The value max must be given and must be an upper bound on the values of lambda(x,y) for all locations (x, y) inside the window win. To generate an inhomogeneous Poisson process the algorithm uses rejection filtering'': it first generates a uniform Poisson process of intensity max, then thins it by randomly deleting or retaining each point independently, with retention probability $p(x,y) = \lambda(x,y)/\mbox{max}$.

Value

• The simulated point pattern (an object of class "ppp").

ppp.object, owin.object

• rpoispp
Examples
# uniform Poisson process with intensity 100 in the unit square
pp <- rpoispp(100)

# uniform Poisson process with intensity 1 in a 10 x 10 square
pp <- rpoispp(1, win=owin(c(0,10),c(0,10)))
# plots should look similar !

# inhomogeneous Poisson process in unit square
# with intensity lambda(x,y) = 100 * exp(-3*x)
# Intensity is bounded by 100
pp <- rpoispp(function(x,y) {100 * exp(-3*x)}, 100)
Documentation reproduced from package spatstat, version 1.0-1, License: GPL version 2 or newer

Community examples

Looks like there are no examples yet.