Package: stlnpp 0.4.0

stlnpp: Spatio-Temporal Analysis of Point Patterns on Linear Networks

Statistical analysis of spatio-temporal point processes on linear networks. This packages provides tools to visualise and analyse spatio-temporal point patterns on linear networks using first- and second-order summary statistics.

Authors:Mehdi Moradi [aut, cre], Ottmar Cronie [ctb], Jorge Mateu [ctb]

stlnpp_0.4.0.tar.gz
stlnpp_0.4.0.zip(r-4.5)stlnpp_0.4.0.zip(r-4.4)stlnpp_0.4.0.zip(r-4.3)
stlnpp_0.4.0.tgz(r-4.4-any)stlnpp_0.4.0.tgz(r-4.3-any)
stlnpp_0.4.0.tar.gz(r-4.5-noble)stlnpp_0.4.0.tar.gz(r-4.4-noble)
stlnpp_0.4.0.tgz(r-4.4-emscripten)stlnpp_0.4.0.tgz(r-4.3-emscripten)
stlnpp.pdf |stlnpp.html✨
stlnpp/json (API)

# Install 'stlnpp' in R:
install.packages('stlnpp', repos = c('https://moradii.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/moradii/stlnpp/issues

Datasets:

On CRAN:

intensityk-functionlinear-networkpair-correlationpoint-pattern-analysisspatio-temporal-analysis

13 exports 12 stars 1.97 score 20 dependencies 1 dependents 272 downloads

Last updated 4 months agofrom:2219c61ecf. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 02 2024
R-4.5-winNOTESep 02 2024
R-4.5-linuxNOTESep 02 2024
R-4.4-winOKSep 02 2024
R-4.4-macOKSep 02 2024
R-4.3-winOKSep 02 2024
R-4.3-macOKSep 02 2024

Exports:as.lpp.stlppas.stlppas.tpp.stlppas.tppint.stlppintrpoistlpprpoistpprthin.stlppSTLgSTLginhomSTLKSTLKinhomstlpptpp

Dependencies:abinddeldirgoftestlatticeMatrixmgcvnlmepolycliprpartspatstatspatstat.dataspatstat.explorespatstat.geomspatstat.linnetspatstat.modelspatstat.randomspatstat.sparsespatstat.univarspatstat.utilstensor

Readme and manuals

Help Manual

Help pageTopics
Methods for spatio-temporal point patterns on a linear networkas.lpp.stlpp
Convert data to a spatio-temporal point pattern on a linear networkas.stlpp
Convert data to a one-dimensional point patternas.tpp.stlpp
Kernel estimation of intensity of spatio-temporal point patterns on a linear networkdensity.stlpp
Kernel estimation of intensity of one-dimensional point patternsdensity.tpp
Intensity estimate of spatio-temporal point pattern using Voronoi-Dirichlet tessellationdensityVoronoi.stlpp
Intensity estimate of temporal point patterns using Voronoi-Dirichlet tessellationdensityVoronoi.tpp
Eastbourne traffic accident dataEastbourne
A simple linear networkeasynet
Medellin traffic accident dataMedellin
Methods for space-time point patterns on a linear networkas.data.frame.sumstlpp as.linim.stlppint as.tppint.stlppint methods.stlpp plot.stlpp plot.stlppint plot.sumstlpp print.stlpp print.stlppint print.sumstlpp [.stlpp [.stlppint
Methods for one-dimensional point patternsmethods.tpp plot.tpp plot.tppint print.tpp print.tppint [.tpp [.tppint
Simulating spatio-temporal Poisson point processes on a linear networkrpoistlpp
Simulating one-dimensional Poisson point patternsrpoistpp
Random thinningrthin.stlpp
Pair correlation function for spatio-temporal point processes on linear networksSTLg
Inhomogeneous pair correlation function for spatio-temporal point processes on linear networksSTLginhom
K-function for spatio-temporal point processes on linear networksSTLK
Inhomogeneous K-function for spatio-temporal point processes on linear networksSTLKinhom
Create spatio-temporal point pattern on linear networkstlpp
Create a temporal point patterntpp
Extract unique points from a spatio-temporal point pattern on a linear networkunique.stlpp