BRIEF DESCRIPTION OF spatstat
This webpage contains spatstat,
a contributed library in R
for the statistical analysis of
spatial point patterns, written by
Adrian Baddeley
and Rolf Turner.
The package supports
- display and manipulation of point patterns in the plane
- exploratory data analysis
- simulation
- parametric model-fitting
- diagnostic plots for a fitted model
- hypothesis tests
The window of observation for the point pattern may have arbitrary shape
(represented by a binary image mask, a polygon, or several polygons
with holes).
The points of the pattern may have marks.
Point process models can be fitted to point pattern data,
using a generic fitting function ppm analogous to
lm, glm, gam.
The point process model is specified using an S language
formula.
The model may be any point process that has a
conditional intensity which is of `exponential family' form,
including spatial trend, dependence on covariates, dependence on marks,
and interpoint interactions of arbitrary order.
For example
ppm(data, ~1, Strauss(r=0.1), .....)
will fit the stationary Strauss process with interaction radius 0.1,
ppm(data, ~polynom(x,y,3), Poisson(), ......)
will fit a nonstationary Poisson process whose intensity function
is log-cubic in the Cartesian coordinates.
Last modified: 30 may 2005