| spatstat.Knet-package {spatstat.Knet} | R Documentation |
Extension to 'spatstat' for Large Datasets on a Linear Network
Description
Extension to the 'spatstat' family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019).
Details
This is an extension to the spatstat package for the analysis of large data sets on linear networks.
Its main functionality is a memory-efficient algorithm
for computing the estimate of the K function
on a linear network, described in Rakshit et al (2019).
The main functions are Knet and Knetinhom.
These are counterparts of the functions
linearK
and
linearKinhom
in the spatstat.linnet package.
The spatstat.linnet functions
linearK
and
linearKinhom
are usable (and slightly faster)
for small datasets, but require substantial amounts of memory.
For larger datasets,
the functions Knet and Knetinhom
are much more efficient.
The DESCRIPTION file:
| Package: | spatstat.Knet |
| Type: | Package |
| Title: | Extension to 'spatstat' for Large Datasets on a Linear Network |
| Version: | 3.1-0 |
| Date: | 2024-07-16 |
| Depends: | R (>= 3.5.0), spatstat.data (>= 3.1-0), spatstat.sparse (>= 3.1-0), spatstat.univar (>= 3.0-0), spatstat.geom (>= 3.3-0), spatstat.random (>= 3.3-0), spatstat.explore (>= 3.3-0), spatstat.model (>= 3.3-0), spatstat.linnet (>= 3.2-0), spatstat (>= 3.1-1) |
| Imports: | spatstat.utils (>= 3.0-5), Matrix |
| Authors@R: | c(person(given="Suman", family="Rakshit", role = c("aut", "cph"), email = "suman.rakshit@curtin.edu.au", comment=c(ORCID="0000-0003-0052-128X")), person(given="Adrian", family="Baddeley", role = c("cre", "cph"), email = "Adrian.Baddeley@curtin.edu.au", comment = c(ORCID="0000-0001-9499-8382"))) |
| Maintainer: | Adrian Baddeley <Adrian.Baddeley@curtin.edu.au> |
| Description: | Extension to the 'spatstat' family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019). |
| License: | GPL (>= 2) |
| NeedsCompilation: | yes |
| ByteCompile: | true |
| Author: | Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>) |
Index of help topics:
Knet Geometrically-Corrected K Function on Network
Knetinhom Geometrically-Corrected Inhomogeneous K
Function on Network
spatstat.Knet-package Extension to 'spatstat' for Large Datasets on a
Linear Network
wacrashes Road Accidents in Western Australia
Author(s)
Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>)
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
References
Rakshit, S., Baddeley, A. and Nair, G. (2019)
Efficient code for second order analysis of events on a linear network.
Journal of Statistical Software 90 (1) 1–37.
DOI: 10.18637/jss.v090.i01