spatstat (version 1.13-0)

rmhstart: Determine Initial State for Metropolis-Hastings Simulation.

Description

Builds a description of the initial state for the Metropolis-Hastings algorithm.

Usage

rmhstart(start, ...)
   ## S3 method for class 'default':
rmhstart(start=NULL, \dots, n.start=NULL, x.start=NULL, iseed)

Arguments

start

An existing description of the initial state in some format. Incompatible with the arguments listed below.

...

There should be no other arguments.

n.start

Number of initial points (to be randomly generated). Incompatible with x.start.

x.start

Initial point pattern configuration. Incompatible with n.start.

iseed

Vector of 3 integers determining the initial state of the random number generator. This argument should not be specified, in normal use.

Value

• An object of class "rmhstart", which is essentially a list of parameters describing the initial point pattern and (optionally) the initial state of the random number generator. There is a print method for this class, which prints a sensible description of the initial state.

Warnings

If iseed is specified, this will fix the initial state of the random number generator in any subsequent call to rmh.

Details

Simulated realisations of many point process models can be generated using the Metropolis-Hastings algorithm implemented in rmh. This function rmhstart creates a full description of the initial state of the Metropolis-Hastings algorithm, including possibly the initial state of the random number generator, for use in a subsequent call to rmh. It also checks that the initial state is valid.

The initial state should be specified either by the first argument start or by the other arguments n.start, x.start etc. If start is a list, then it should have components named n.start or x.start and optionally iseed, with the same interpretation as described below.

The arguments are: [object Object],[object Object],[object Object] The parameters n.start and x.start are incompatible.

See Also

rmh, rmhcontrol, rmhmodel

Examples

# 30 random points
   a <- rmhstart(n.start=30)

   # a particular point pattern
   data(cells)
   b <- rmhstart(x.start=cells)

   # set the seed
   d <- rmhstart(n.start=30, iseed=c(42, 4, 2))