The spatstat.linnet Package
The spatstat.linnet package belongs to the spatstat family of packages. It contains the functionality for analysing spatial data on a linear network.
spatstat is a family of R packages for the statistical analysis of spatial data. Its main focus is the analysis of spatial patterns of points in two-dimensional space.
The original spatstat package has now been split into several sub-packages.
This sub-package spatstat.linnet contains the user-level functions from spatstat that are concerned with spatial data on a linear network.
The orginal spatstat package grew to be very large. It has now been divided into several sub-packages:
spatstat.utils containing basic utilities
spatstat.sparse containing linear algebra utilities
spatstat.data containing datasets
spatstat.geom containing geometrical objects and geometrical operations
spatstat.core containing the main functionality for statistical analysis and modelling of spatial data
spatstat.linnet containing functions for spatial data on a linear network
spatstat, which simply loads the other sub-packages listed above, and provides documentation.
When you install spatstat, these sub-packages are also
installed. Then if you load the spatstat package by typing
library(spatstat), the other sub-packages listed above will
automatically be loaded or imported.
For an overview of all the functions available in these sub-packages,
see the help file for spatstat in the spatstat package,
Additionally there are several extension packages:
spatstat.gui for interactive graphics
spatstat.local for local likelihood (including geographically weighted regression)
spatstat.Knet for additional, computationally efficient code for linear networks
spatstat.sphere (under development) for spatial data on a sphere, including spatial data on the earth's surface
The extension packages must be installed separately and loaded explicitly if needed. They also have separate documentation.
Here is a list of the main functionality in spatstat.linnet.
Point patterns on a linear network
An object of class "linnet" represents a linear network
(for example, a road network).
linnet |
create a linear network |
clickjoin |
interactively join vertices in network |
spatstat.gui::iplot.linnet |
interactively plot network |
simplenet |
simple example of network |
lineardisc |
disc in a linear network |
delaunayNetwork |
network of Delaunay triangulation |
dirichletNetwork |
network of Dirichlet edges |
methods.linnet |
methods for linnet objects |
vertices.linnet |
nodes of network |
joinVertices |
join existing vertices in a network |
insertVertices |
insert new vertices at positions along a network |
addVertices |
add new vertices, extending a network |
thinNetwork |
remove vertices or lines from a network |
repairNetwork |
repair internal format |
pixellate.linnet |
approximate by pixel image |
An object of class "lpp" represents a
point pattern on a linear network (for example,
road accidents on a road network).
lpp |
create a point pattern on a linear network |
methods.lpp |
methods for lpp objects |
subset.lpp |
method for subset |
rpoislpp |
simulate Poisson points on linear network |
runiflpp |
simulate random points on a linear network |
chicago |
Chicago crime data |
dendrite |
Dendritic spines data |
spiders |
Spider webs on mortar lines of brick wall |
Summary statistics for a point pattern on a linear network:
These are for point patterns on a linear network (class lpp).
For unmarked patterns:
linearK |
K function on linear network |
linearKinhom |
inhomogeneous K function on linear network |
linearpcf |
pair correlation function on linear network |
linearpcfinhom |
inhomogeneous pair correlation on linear network |
For multitype patterns:
linearKcross |
K function between two types of points |
linearKdot |
K function from one type to any type |
linearKcross.inhom |
Inhomogeneous version of linearKcross |
linearKdot.inhom |
Inhomogeneous version of linearKdot |
linearmarkconnect |
Mark connection function on linear network |
linearmarkequal |
Mark equality function on linear network |
linearpcfcross |
Pair correlation between two types of points |
linearpcfdot |
Pair correlation from one type to any type |
linearpcfcross.inhom |
Inhomogeneous version of linearpcfcross |
linearpcfdot.inhom |
Inhomogeneous version of linearpcfdot
|
Related facilities:
pairdist.lpp |
distances between pairs |
crossdist.lpp |
distances between pairs |
nndist.lpp |
nearest neighbour distances |
nncross.lpp |
nearest neighbour distances |
nnwhich.lpp |
find nearest neighbours |
nnfun.lpp |
find nearest data point |
density.lpp |
kernel smoothing estimator of intensity |
distfun.lpp |
distance transform |
envelope.lpp |
simulation envelopes |
rpoislpp |
simulate Poisson points on linear network |
runiflpp |
simulate random points on a linear network |
It is also possible to fit point process models to lpp objects.
Point process models on a linear network:
An object of class "lpp" represents a pattern of points on
a linear network. Point process models can also be fitted to these
objects. Currently only Poisson models can be fitted.
lppm |
point process model on linear network |
anova.lppm |
analysis of deviance for |
| point process model on linear network | |
envelope.lppm |
simulation envelopes for |
| point process model on linear network | |
fitted.lppm |
fitted intensity values |
predict.lppm |
model prediction on linear network |
linim |
pixel image on linear network |
plot.linim |
plot a pixel image on linear network |
eval.linim |
evaluate expression involving images |
linfun |
function defined on linear network |
methods.linfun |
conversion facilities |
This library and its documentation are usable under the terms of the "GNU General Public License", a copy of which is distributed with the package.
Ottmar Cronie, Tilman Davies, Greg McSwiggan and Suman Rakshit made substantial contributions of code.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
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