spatstat: The Spatstat Package
Description
This is a summary of the features of
spatstat, a package in R
for the statistical analysis of spatial point patterns.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.
FUNCTIONS AND DATASETS
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.
CONTENTS:
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
}Details
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.