Dear Terry
the R package 'spatstat' contains a large number of functions for
generating point patterns with varying degrees of randomness or orderliness.
They include:
rpoint n independent random points
rpoispp random number of independent random points
rstrat stratified random pattern (k points in each box)
rsyst systematic random pattern (randomly placed grid)
rThomas Thomas cluster model
rMatClust Matern Cluster model
rNeymanScott Neyman-Scott cluster model
rcell Baddeley-Silverman cell process
rmh Gibbs point processes (Strauss, Geyer etc)
Several of your correspondents have suggested using the normal distribution
to make clumps of points. This is what the `Thomas' model does - it first
generates a random pattern of centre points, then around each centre, it
generates a clump of points with Normally distributed displacements from
the centre point.
The Matern cluster model is a similar thing, but instead of the points
being Normally distributed around each centre, they are uniformly distributed
inside a circle around the centre point.
One of the replies suggested using the Strauss process. This does not
produce clumps. You can get weakly clumped point patterns from the Geyer
process and some of the other Gibbs processes offered in 'rmh', but in general
this is not the best way to create clumps.
Hope this helps
Adrian Baddeley
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