Generate Random Numbers of Points for Cell Process
Generates random integers for the Baddeley-Silverman counterexample.
rcellnumber(n, N = 10, mu=1)
n |
Number of random integers to be generated. |
N |
Distributional parameter: the largest possible value
(when |
mu |
Mean of the distribution (equals the variance). Any positive real number. |
If mu = 1 (the default),
this function generates random integers which have mean and variance
equal to 1, but which do not have a Poisson distribution.
The random integers take the values 0, 1 and N
with probabilities 1/N, (N-2)/(N-1) and 1/(N(N-1))
respectively.
See Baddeley and Silverman (1984).
If mu is another positive number, the random integers will
have mean and variance equal to mu. They are obtained by
generating the
one-dimensional counterpart of the cell process and counting the
number of points in the interval from 0 to mu. The
maximum possible value of each random integer is N * ceiling(mu).
An integer vector of length n.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
Baddeley, A.J. and Silverman, B.W. (1984) A cautionary example on the use of second-order methods for analyzing point patterns. Biometrics 40, 1089-1094.
rcellnumber(30, 3)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.