The Spatstat Package

This is a summary of the features of spatstat, a package in R for the statistical analysis of spatial point patterns.


spatstat is a package for the statistical analysis of spatial data. Currently, it deals mainly with the analysis of patterns of points in the plane. The points may carry `marks', and the spatial region in which the points were recorded may have arbitrary shape.

The package supports

  • creation, manipulation and plotting of point patterns
  • exploratory data analysis
  • simulation of point process models
  • parametric model-fitting
  • hypothesis tests and diagnostics
The point process models to be fitted may be quite general Gibbs/Markov models; they may include spatial trend, dependence on covariates, and interpoint interactions of any order (i.e. not restricted to pairwise interactions). Models are specified by a formula in the R language, and are fitted using a single function ppm analogous to lm and glm. It is also possible to fit cluster process models by the method of minimum contrast.

Getting Started

For a quick introduction to spatstat, see the paper by Baddeley and Turner (2005a). For a complete 2-day course on using spatstat, see the workshop notes by Baddeley (2008). Both of these documents are available on the internet.

Type demo(spatstat) for a demonstration of the package's capabilities. Type demo(data) to see all the datasets available in the package.


Following is a summary of the main functions and datasets in the spatstat package. Alternatively an alphabetical list of all functions and datasets is available by typing library(help=spatstat).

For further information on any of these, type help(name) where name is the name of the function or dataset.


ll{ I. Creating and manipulating data II. Exploratory Data Analysis III. Model fitting (cluster models) IV. Model fitting (Gibbs models) V. Tests and diagnostics VI. Documentation }

  • spatstat-package
  • spatstat
Documentation reproduced from package spatstat, version 1.14-7, License: GPL (>= 2)

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