https://github.com/spatstat/spatstat.random

Sub-package of spatstat containing functions for random generation
https://github.com/spatstat/spatstat.random

point-processes random-generation simulation spatial-sampling spatial-simulation

Last synced: 13 days ago
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Sub-package of spatstat containing functions for random generation

• Host: GitHub
• URL: https://github.com/spatstat/spatstat.random
• Owner: spatstat
• Created: 2022-01-03T11:22:27.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2025-10-09T15:00:12.000Z (26 days ago)
• Last Synced: 2025-10-21T20:57:23.535Z (13 days ago)
• Topics: point-processes, random-generation, simulation, spatial-sampling, spatial-simulation
• Language: R
• Homepage:
• Size: 866 KB
• Stars: 5
• Watchers: 3
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS

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README

          
# spatstat.random

## Random Generation and Simulation for the spatstat family

[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/spatstat.random)](http://CRAN.R-project.org/package=spatstat.random) 

[![GitHub R package version](https://img.shields.io/github/r-package/v/spatstat/spatstat.random)](https://github.com/spatstat/spatstat.random)

The original `spatstat` package has been split into

several sub-packages.

This package `spatstat.random` is one of these packages.

It contains the functions for

- generating random spatial patterns of points according to many simple rules

(complete spatial randomness, binomial process, random grid,

systematic random, stratified random, 

simple sequential inhibition, cell process),

- randomised alteration of patterns (thinning,

random shift, jittering),

- generating simulated realisations of spatial point processes

(Poisson processes, Matern inhibition models, Matern cluster processes,

Neyman-Scott cluster processes, log-Gaussian Cox processes,

product shot noise cluster processes, Gibbs point processes)

- generating simulated realisations of Gibbs point processes

(Metropolis-Hastings birth-death-shift algorithm;

perfect simulation/ dominated coupling from the past;

alternating Gibbs sampler)

- generating random spatial patterns of line segments

- generating random tessellations

- generating random images (random noise, random mosaics).

Exceptions:

- generation of determinantal point processes is provided in `spatstat.model`

- generation of quasi-random patterns is provided in `spatstat.geom`

The reorganisation of `spatstat` into a family of packages is described

on the GitHub repository

[spatstat/spatstat](https://github.com/spatstat/spatstat).