R: Alternating Gibbs Sampler for Multitype Point Processes

rags {spatstat.core} | R Documentation

## Alternating Gibbs Sampler for Multitype Point Processes

### Description

Simulate a realisation of a point process model using the alternating Gibbs sampler.

### Usage

    rags(model, ..., ncycles = 100)

### Arguments

`model` | Data specifying some kind of point process model.
`...` | Additional arguments passed to other code.
`ncycles` | Number of cycles of the alternating Gibbs sampler that should be performed.

### Details

The Alternating Gibbs Sampler for a multitype point process is an iterative simulation procedure. Each step of the sampler updates the pattern of points of a particular type `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.

The argument `model` should be an object describing a point process model. At the moment, the only permitted format for `model` is of the form `list(beta, hradii)` where `beta` gives the first order trend and `hradii` is the matrix of interaction radii. See `ragsMultiHard` for full details.

### Value

A point pattern (object of class `"ppp"`).

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

### See Also

`ragsMultiHard`, `ragsAreaInter`

### Examples

      mo <- list(beta=c(30, 20),
                 hradii = 0.05 * matrix(c(0,1,1,0), 2, 2))
      rags(mo, ncycles=10)

[Package spatstat.core version 2.3-0 Index]