The original spatstat package has been split into several sub-packages
(See spatstat/spatstat).
This package spatstat.linnet is one of the sub-packages.
It contains the subset of the functionality of spatstat
that deals with data on linear networks.
spatstat.linnet supports
- examples of linear networks
- creation of linear networks from coordinate data
- extraction of networks from tessellations
- modification of networks
- interactive editing of networks
- geometrical operations and measurement on networks
- construction of the disc in the shortest-path metric
- trees, tree branch labels, tree pruning
- examples of point patterns on linear networks
- creation of point patterns on a network from coordinate data
- extraction of sub-patterns
- shortest-path distance measurement
- create pixel images and functions on a network
- arithmetic operators for pixel images on a network
- plot pixel images on a network (colour/thickness/perspective)
- tessellation on a network
- completely random (uniform Poisson) point patterns on a network
- nonuniform random (Poisson) point patterns on a network
- Switzer-type point process
- log-Gaussian Cox process
- kernel density estimation on a network
- bandwidth selection
- kernel smoothing on a network
- estimation of intensity as a function of a covariate
- ROC curves
- Berman-Waller-Lawson test
- CDF test
- variable selection by Sufficient Dimension Reduction
- K function on a network (shortest path or Euclidean distance)
- pair correlation function on a network (shortest path or Euclidean distance)
- inhomogeneous K function and pair correlation function
- inhomogeneous F, G and J functions
- simulation envelopes of summary functions
- fit point process model on a network
- fitted/predicted intensity
- analysis of deviance for point process model
- simulate fitted model