ragsMultiHard(beta, hradii, ..., types=NULL, bmax = NULL, periodic=FALSE, ncycles = 100)0 or NA.
  rmpoispp
    when generating random points. 
beta.
  "ppp").
i,
  by drawing a realisation from the conditional distribution of
  points of type i given the points of all other types.
  Successive steps of the sampler update the points of type 1, then
  type 2, type 3, and so on.   This is an experimental implementation which currently works only
  for multitype hard core processes (see MultiHard)
  in which there is no interaction between points of the same type,
  and for the area-interaction process (see ragsAreaInter).
  The argument beta gives the first order trend for
  each possible type of point. It may be a single number, a numeric
  vector, a function(x,y), a pixel image, a list of functions,
  a function(x,y,m), or a list of pixel images. 
  The argument hradii is the matrix of hard core radii
  between each pair of possible types of points. Two points of types
  i and j respectively are forbidden to lie closer than
  a distance hradii[i,j] apart. The diagonal of this matrix must
  contain NA or 0 values, indicating that there is no hard
  core constraint applying between points of the same type.
rags,
  ragsAreaInter
  b <- c(30,20)
  h <- 0.05 * matrix(c(0,1,1,0), 2, 2)
  ragsMultiHard(b, h, ncycles=10)
  ragsMultiHard(b, h, ncycles=5, periodic=TRUE)
Run the code above in your browser using DataLab