# rmhstart

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##### Determine Initial State for Metropolis-Hastings Simulation.

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

Keywords
spatial, datagen
##### Usage
rmhstart(start, ...)
## S3 method for class 'default':
rmhstart(start=NULL, \dots, n.start=NULL, x.start=NULL)
##### 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.
##### 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, with the same interpretation as described below.

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

##### 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.

rmh, rmhcontrol, rmhmodel

##### Aliases
• rmhstart
• rmhstart.default
##### Examples
# 30 random points
a <- rmhstart(n.start=30)

# a particular point pattern
data(cells)
b <- rmhstart(x.start=cells)
Documentation reproduced from package spatstat, version 1.25-5, License: GPL (>= 2)

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