# Random Generation Functionality for the 'spatstat' Family

## Documentation for package ‘spatstat.random’ version 3.4-5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

A C D E G I M P Q R S U W

spatstat.random-package | The spatstat.random Package

## -- A --

as.owin.rmhmodel | Convert Data To Class owin

## -- C --

clusterfield | Field of clusters
clusterfield.character | Field of clusters
clusterfield.function | Field of clusters
clusterkernel | Extract Cluster Offspring Kernel
clusterkernel.character | Extract Cluster Offspring Kernel
clusterprocess | Cluster Point Process Model
clusterradius | Compute or Extract Effective Range of Cluster Kernel
clusterradius.character | Compute or Extract Effective Range of Cluster Kernel
clusterradius.clusterprocess | Methods for Cluster Models

## -- D --

default.expand | Default Expansion Rule for Simulation of Model
default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm.
dknn | Theoretical Distribution of Nearest Neighbour Distance
dmixpois | Mixed Poisson Distribution
domain.rmhmodel | Extract the Domain of any Spatial Object
dpakes | Pakes distribution

## -- E --

expand.owin | Apply Expansion Rule

## -- G --

gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution

## -- I --

intensity.clusterprocess | Methods for Cluster Models
is.poisson | Recognise Stationary and Poisson Point Process Models
is.poisson.rmhmodel | Recognise Stationary and Poisson Point Process Models
is.stationary | Recognise Stationary and Poisson Point Process Models
is.stationary.rmhmodel | Recognise Stationary and Poisson Point Process Models

## -- M --

methods.clusterprocess | Methods for Cluster Models

## -- P --

pknn | Theoretical Distribution of Nearest Neighbour Distance
pmixpois | Mixed Poisson Distribution
ppakes | Pakes distribution
predict.clusterprocess | Methods for Cluster Models
print.clusterprocess | Methods for Cluster Models

## -- Q --

qknn | Theoretical Distribution of Nearest Neighbour Distance
qmixpois | Mixed Poisson Distribution
qpakes | Pakes distribution
quadratresample | Resample a Point Pattern by Resampling Quadrats

## -- R --

rags | Alternating Gibbs Sampler for Multitype Point Processes
ragsAreaInter | Alternating Gibbs Sampler for Area-Interaction Process
ragsMultiHard | Alternating Gibbs Sampler for Multitype Hard Core Process
rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel
rcell | Simulate Baddeley-Silverman Cell Process
rcellnumber | Generate Random Numbers of Points for Cell Process
rclusterBKBC | Simulate Cluster Process using Brix-Kendall Algorithm or Modifications
rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process
rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process
reach | Interaction Distance of a Point Process Model
reach.clusterprocess | Methods for Cluster Models
reach.rmhmodel | Interaction Distance of a Point Process Model
recipEnzpois | First Reciprocal Moment of the Truncated Poisson Distribution
rGaussPoisson | Simulate Gauss-Poisson Process
rGRFexpo | Simulate a Gaussian Random Field
rGRFgauss | Simulate a Gaussian Random Field
rGRFgencauchy | Simulate a Gaussian Random Field
rGRFmatern | Simulate a Gaussian Random Field
rGRFstable | Simulate a Gaussian Random Field
rHardcore | Perfect Simulation of the Hardcore Process
rjitter.psp | Random Perturbation of Line Segment Pattern
rknn | Theoretical Distribution of Nearest Neighbour Distance
rlabel | Random Re-Labelling of Point Pattern
rLGCP | Simulate Log-Gaussian Cox Process
rMatClust | Simulate Matern Cluster Process
rMaternI | Simulate Matern Model I
rMaternII | Simulate Matern Model II
rmh | Simulate point patterns using the Metropolis-Hastings algorithm.
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm.
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm.
rmhcontrol.default | Set Control Parameters for Metropolis-Hastings Algorithm.
rmhexpand | Specify Simulation Window or Expansion Rule
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation.
rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation.
rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation.
rmhstart | Determine Initial State for Metropolis-Hastings Simulation.
rmhstart.default | Determine Initial State for Metropolis-Hastings Simulation.
rmixpois | Mixed Poisson Distribution
rMosaicField | Mosaic Random Field
rMosaicSet | Mosaic Random Set
rmpoint | Generate N Random Multitype Points
rmpoispp | Generate Multitype Poisson Point Pattern
rNeymanScott | Simulate Neyman-Scott Process
rnoise | Random Pixel Noise
rpakes | Pakes distribution
rPenttinen | Perfect Simulation of the Penttinen Process
rpoint | Generate N Random Points
rpoint3 | Generate N Random Points in 3 Dimensions
rpoisline | Generate Poisson Random Line Process
rpoislinetess | Poisson Line Tessellation
rpoisnonzero | Random Values from the Truncated Poisson Distribution
rpoispp | Generate Poisson Point Pattern
rpoispp3 | Generate Poisson Point Pattern in Three Dimensions
rpoisppOnLines | Generate Poisson Point Pattern on Line Segments
rpoisppx | Generate Poisson Point Pattern in Any Dimensions
rPoissonCluster | Simulate Poisson Cluster Process
rpoistrunc | Random Values from the Truncated Poisson Distribution
rPSNCP | Simulate Product Shot-noise Cox Process
rshift | Random Shift
rshift.ppp | Randomly Shift a Point Pattern
rshift.psp | Randomly Shift a Line Segment Pattern
rshift.splitppp | Randomly Shift a List of Point Patterns
rSSI | Simulate Simple Sequential Inhibition
rstrat | Simulate Stratified Random Point Pattern
rStrauss | Perfect Simulation of the Strauss Process
rStraussHard | Perfect Simulation of the Strauss-Hardcore Process
rtemper | Simulated Annealing or Simulated Tempering for Gibbs Point Processes
rthin | Random Thinning
rthinclumps | Random Thinning of Clumps
rThomas | Simulate Thomas Process
runifdisc | Generate N Uniform Random Points in a Disc
runifpoint | Generate N Uniform Random Points
runifpoint3 | Generate N Uniform Random Points in Three Dimensions
runifpointOnLines | Generate N Uniform Random Points On Line Segments
runifpointx | Generate N Uniform Random Points in Any Dimensions
rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel

## -- S --

simulate.clusterprocess | Methods for Cluster Models
spatstat.random | The spatstat.random Package

## -- U --

update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm

## -- W --

will.expand | Test Expansion Rule
Window.rmhmodel | Extract Window of Spatial Object