R: Generate Random Numbers of Points for Cell Process

rcellnumber {spatstat.core} | R Documentation

## Generate Random Numbers of Points for Cell Process

### Description

Generates random integers for the Baddeley-Silverman counterexample.

### 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`.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### 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.

### See Also

`rcell`

### Examples

       rcellnumber(30, 3)

[Package spatstat.core version 2.3-0 Index]