spatstat.linnet-package: The spatstat.linnet Package
In spatstat.linnet: Linear Networks Functionality of the 'spatstat' Family

spatstat.linnet-package

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.explore containing the main functionality for exploratory and non-parametric analysis of spatial data
spatstat.model containing the main functionality for statistical modelling and inference for 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