# rcellnumber

0th

Percentile

##### Generate Random Numbers of Points for Cell Process

Generates random integers for the Baddeley-Silverman counterexample.

Keywords
datagen
##### Usage
rcellnumber(n, N = 10, mu=1)
##### Arguments
n

Number of random integers to be generated.

N

Distributional parameter: the largest possible value (when mu <= 1). An integer greater than 1.

mu

Mean of the distribution (equals the variance). Any positive real number.

##### Details

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).

##### Value

An integer vector of length n.

##### References

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.

rcell

• rcellnumber
##### Examples
# NOT RUN {
rcellnumber(30, 3)
# }

Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)

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