spatstat.random3.4-3 package

Convert Data To Class owin

Field of clusters

Extract Cluster Offspring Kernel

Compute or Extract Effective Range of Cluster Kernel

Default Expansion Rule for Simulation of Model

Set Default Control Parameters for Metropolis-Hastings Algorithm.

Mixed Poisson Distribution

Extract the Domain of any Spatial Object

Pakes distribution

Apply Expansion Rule

Gauss-Hermite Quadrature Approximation to Expectation for Normal Distr...

Recognise Stationary and Poisson Point Process Models

Resample a Point Pattern by Resampling Quadrats

Alternating Gibbs Sampler for Multitype Point Processes

Alternating Gibbs Sampler for Area-Interaction Process

Alternating Gibbs Sampler for Multitype Hard Core Process

Simulate Neyman-Scott Point Process with Cauchy cluster kernel

Simulate Baddeley-Silverman Cell Process

Generate Random Numbers of Points for Cell Process

Simulate Cluster Process using Brix-Kendall Algorithm or Modifications

Perfect Simulation of the Diggle-Gates-Stibbard Process

Perfect Simulation of the Diggle-Gratton Process

Interaction Distance of a Point Process Model

First Reciprocal Moment of the Truncated Poisson Distribution

Simulate Gauss-Poisson Process

Simulate a Gaussian Random Field

Perfect Simulation of the Hardcore Process

Random Perturbation of Line Segment Pattern

Theoretical Distribution of Nearest Neighbour Distance

Random Re-Labelling of Point Pattern

Simulate Log-Gaussian Cox Process

Simulate Matern Cluster Process

Simulate Matern Model I

Simulate Matern Model II

Simulate Point Process Models using the Metropolis-Hastings Algorithm.

Simulate point patterns using the Metropolis-Hastings algorithm.

Set Control Parameters for Metropolis-Hastings Algorithm.

Specify Simulation Window or Expansion Rule

Build Point Process Model for Metropolis-Hastings Simulation.

Define Point Process Model for Metropolis-Hastings Simulation.

Define Point Process Model for Metropolis-Hastings Simulation.

Determine Initial State for Metropolis-Hastings Simulation.

Mosaic Random Field

Mosaic Random Set

Generate N Random Multitype Points

Generate Multitype Poisson Point Pattern

Simulate Neyman-Scott Process

Random Pixel Noise

Perfect Simulation of the Penttinen Process

Generate N Random Points

Generate Poisson Random Line Process

Poisson Line Tessellation

Generate Poisson Point Pattern

Generate Poisson Point Pattern in Three Dimensions

Generate Poisson Point Pattern on Line Segments

Generate Poisson Point Pattern in Any Dimensions

Simulate Poisson Cluster Process

Random Values from the Truncated Poisson Distribution

Simulate Product Shot-noise Cox Process

Randomly Shift a Point Pattern

Randomly Shift a Line Segment Pattern

Random Shift

Randomly Shift a List of Point Patterns

Simulate Simple Sequential Inhibition

Simulate Stratified Random Point Pattern

Perfect Simulation of the Strauss Process

Perfect Simulation of the Strauss-Hardcore Process

Simulated Annealing or Simulated Tempering for Gibbs Point Processes

Random Thinning

Random Thinning of Clumps

Simulate Thomas Process

Generate N Uniform Random Points in a Disc

Generate N Uniform Random Points

Generate N Uniform Random Points in Three Dimensions

Generate N Uniform Random Points On Line Segments

Generate N Uniform Random Points in Any Dimensions

Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel

Internal spatstat.random functions

The spatstat.random Package

Update Control Parameters of Metropolis-Hastings Algorithm

Test Expansion Rule

Extract Window of Spatial Object