[FORGED] Spatial points pattern generation

Hello everybody, working with the spatstat package I would need to generate
some artificial spatial points pattern with an associate mark. More in
detail I would like to create 3 or 4 examples with approximately 1000 trees
on a square of 100x100 metres (1 hectare) with

1) Completely random distribution
2) Clustered distribution
3) Regular distribution
4) Mixed distribution

all the points must have an associated mark (e.g. in case of trees a
diameter in centimeters) and the autocorrelation must be detectable (the
exercise is exactly aimed to study the presence of autocorrelation)

"Completely random" patterns can be generated using rpoispp().

Clustered patterns can be generated using (amongst other functions)

   * rThomos()
   * rMatern()
   * rLGCP()

or more generally using rNeymanScott().

Regular patterns can be generated using rmh() with 'cif="strauss"'
or using rStrauss().

Not quite sure what you mean by a "Mixed distribution".  Perhaps you 
want to do something like generate patterns from 1), 2) and 3) and then 
superimpose them into a single pattern using superimpose().

Marks are assigned to points of a pattern by means of the syntax

     marks(X) <- m

where m is a vector or factor of length equal to npoints(X) or a data 
frame with nrows(m) = npoints(X).

How you generate the marks is up to you.

Read the (incredibly well written :-) ) help for the functions referred 
to above, or better still read the (even more incredibly well
written :-) ) book to which you can find a pointer by pointing your 
browser at http://spatstat.github.io.

That's about all I can say in response to such a general question.  If 
you have further focussed and specific questions, please get back to me.

cheers,

Rolf Turner

Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276