R: The spatstat.linnet Package

spatstat.linnet-package {spatstat.linnet} | R Documentation

## The spatstat.linnet Package

### Description

The spatstat.linnet package belongs to the spatstat family of packages. It contains the functionality for analysing spatial data on a linear network.

### Details

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.

### Structure of the spatstat family

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.

### Overview of functionality

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

### Licence

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.

### Acknowledgements

Ottmar Cronie, Tilman Davies, Greg McSwiggan and Suman Rakshit made substantial contributions of code.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

[Package spatstat.linnet version 2.3-1 Index]