R Observatory: Metrics for spatstat.linnet version 3.5-4

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

spatstat.linnet

3.5-4Package record

Linear Networks Functionality of the 'spatstat' Family

14packages dependsuggested by 10

279.2Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Adrian BaddeleyCRAN page ↗GitHub ↗Website ↗Issues ↗

Defines types of spatial data on a linear network and provides functionality for geometrical operations, data analysis and modelling of data on a linear network, in the 'spatstat' family of packages. Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. Data types defined on a network include point patterns, pixel images, functions, and tessellations. Exploratory methods include kernel estimation of intensity on a network, K-functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the function lppm() similar to glm(). Only Poisson models are implemented so far. Models may involve dependence on covariates and dependence on marks. Models are fitted by maximum likelihood. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. Random point patterns on a network can be generated using a variety of models.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("spatstat.linnet", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("spatstat/spatstat.linnet")

Development version from spatstat/spatstat.linnet. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-spatstat.linnet

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-spatstat.linnet

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-spatstat.linnet

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 6.5 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-07-31
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK12 OK2026-04-25

Show 1 earlier changeHide 1 earlier change

NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 3.5-4

README· In the repository, left out of the releaseVignettesNoNEWSYes · 0% structuredCitation fileYes · cites a publicationWebsiteYes

Cites a JSS article

Help pages: 166 (2 internal)includes a package overview page
Examples that run: 100%156 run in a plain check (10 of them under a condition)
Exported functions with examples: 95%
Documented parameters: 84%
Return-value docs: 100%
Help pages citing references: 35%

How these are measured

Downloads

279.2K

CRAN downloads in the past year

Rank #745 · ~765/day · ~23.3K/mo

Releases R versions

Daily download trend is not available in this view yet.

30.4K30 days

68K90 days

279.2K1 year

Compare downloads with other packages →

Also on6.1K r2u11 autocran18.2K conda_forge238 c2d4u

How downloads are counted

Repository

spatstat/spatstat.linnet ↗Organization: spatstat

6Stars

2Forks

1Open issues

0Open PRs

17Releases

270Commits

3Commit identities

network-analysisspatial-data-analysispoint-processesstatistical-modelsstatistical-inferencestatistical-analysiskernel-density-estimationdensity-estimation

270 commits · Last activity 2026-09-25 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 0%
Median days to close, 50 most recently updated closed issues: 1
Median days to close, 50 most recently updated closed PRs: 2

Stars over time

2023-08-04 · 62026-07-07 · 6

How these are measured

PracticesBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/spatstat/spatstat.linnet on 2026-10-22.

Continuous integration (1)

GitHub Actions

Coverage (1)

Coverage reporting

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

11 external dependencies (excludes base and recommended)

Installing spatstat.linnet adds 13 packages (10 with compiled code, 6.0 MB of source tarballs). Heaviest: spatstat.data 2.9 MB, spatstat.model 849 KB, spatstat.geom 816 KB.

Depends (12)

R >= 3.5.0statsgraphicsgrDevicesmethodsutilsspatstat.data spatstat.univar spatstat.geom spatstat.random spatstat.explore spatstat.model

Imports (3)

Matrixspatstat.utils spatstat.sparse

LinkingTo (0)

none

Suggests (3)

goftest locfit spatstat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

14direct

32indirect

Depends 4 · Imports 10

Suggested by 10

Show all 24 packagesHide all 24 packages

Depends, Imports or LinkingTo, most downloaded first

spatstat graph4lg rcarbon stopp SpatialVx spatstat.Knet spatstat.convert DRHotNet stlnpp pphotspot ttbary spatstat.gui kernstadapt markstat

Suggests, most downloaded first

sf spatstat.geom spatstat.random spatstat.explore spatstat.data spatstat.model sftime sfnetworks GET secrlinear

How these are counted

Code & Tests

People & History

People (8)

Adrian Baddeley

Greg McSwiggan

Author, Copyright holder

Ege Rubak

Author, Copyright holder

Rolf Turner

Author, Copyright holder

Ottmar Cronie

Contributor

Tilman Davies

Contributor, Copyright holder

Mehdi Moradi

Contributor, Copyright holder · added in 3.0-2

Suman Rakshit

Contributor, Copyright holder

Releases (29)

Pick two releases to compare their code metrics.

3.5-4Latest
record
2026-09-25 · current release · diff ↗ ·
added 3 exports
rrlppEngine, transect.linfun, transect.linim
3.5-3
record
2026-07-30 · diff ↗ ·
added 1 export
distbdry.lpp
3.5-1
record
2026-05-31 · diff ↗ ·
added 1 export
intensity.lppm
R
R 4.6.0 released · 2026-04-24
3.5-0
record
2026-03-31 · diff ↗ ·
added 1 export
mergeTiles.lintess
3.4-1
record
2026-01-31 · diff ↗ ·
added 4 exports
levelset.linfun, mapLinnetToLine, shortestpath, threads
3.4-0
record
2025-11-29 · diff ↗ ·
added 42 exports
affine.lintess, as.function.linim, as.function.linnet, as.function.lintess, as.linim.function, as.lintess, as.lintess.linearquadratcount, as.lintess.linnet, as.lintess.lintess, as.owin.linearquadratcount, diagLppmEngine, diagnose.lppm, domain.linearquadratcount, eem.lppm, flipxy.linnet, flipxy.lintess, flipxy.lpp, harmonise.linim, harmonize.linim, intensity.linearquadratcount, linim.apply, lurking.lpp, lurking.lppm, marginalIntegralOfLinim, parres.lppm, plot.diaglppm, plot.linearquadratcount, plot.qqlppm, print.diaglppm, print.qqlppm and 12 more
3.3-2
record
2025-09-24 · diff ↗
3.3-1
record
2025-07-24 · diff ↗ ·
added 4 exports
as.linfun.linnet, identify.linnet, identify.lintess, unmark.linnet
3.2-6
record
2025-05-23 · diff ↗
R
R 4.5.0 released · 2025-04-11
3.2-5
record
2025-01-22 · diff ↗
3.2-3
record
2024-11-19 · diff ↗
3.2-2
record
2024-09-20 · diff ↗
3.2-1
record
2024-07-15 · diff ↗ ·
added 10 exports
evaluateNetCovariate, evaluateNetCovariateAlongNetwork, evaluateNetCovariateAtPoints, exactlppm, is.poisson.exactlppm, is.stationary.exactlppm, predict.exactlppm, print.exactlppm, response.exactlppm, spatialCovariateEvidence.exactlppm
R
R 4.4.0 released · 2024-04-24

Show 20 earlier eventsHide 20 earlier events

3.1-5
record
2024-03-25 · diff ↗
3.1-4
record
2024-02-04 · diff ↗ ·
added 5 exports
getglmdata.lppm, getglmfit.lppm, getglmsubset.lppm, hasglmfit.lppm, traceTessLinnet
3.1-3
record
2023-10-28 · diff ↗
3.1-1
record
2023-05-15 · diff ↗
R
R 4.3.0 released · 2023-04-21
3.1-0
record
2023-04-14 · diff ↗
3.0-6
record
2023-02-22 · diff ↗
3.0-4
record
2023-01-27 · diff ↗ ·
added 1 export
quantilefun.linim
3.0-3
record
2022-11-15 · diff ↗
3.0-2
record
2022-11-09 · diff ↗ ·
removed 2 exports
evalCovar.lppm, getlambda.lpp

added 19 exports
bw.relrisk.lpp, distmap.lpp, lineardiscEngine, lineardisclength, linearEuclidEngine, linearJinhom, linearKEuclid, linearKEuclidInhom, linearpcfEuclid, linearpcfEuclidInhom, marks.linnet, marks<-.linnet, resolve.lambda.lpp, rmaxEuclidean, rThomaslpp, Smooth.lpp, spatialCovariateEvidence.lppm, terminalvertices, updateData.lppm
R
R 4.2.0 released · 2022-04-22
2.3-2
record
2022-02-16 · diff ↗
2.3-1
record
2021-12-11 · diff ↗ ·
added 2 exports
circumradius.linnet, rjitter.lpp
2.3-0
record
2021-07-17 · diff ↗ ·
added 4 exports
persp.linfun, persp.linim, response.lppm, sdr.lpp
2.2-1
record
2021-06-22 · diff ↗
R
R 4.1.0 released · 2021-05-18
2.1-1
record
2021-03-28 · diff ↗ ·
removed 1 export
densityHeatlpp

added 2 exports
densityHeat.lpp, rjitterlpp
2.0-0
record
2021-03-18 · diff ↗ ·
removed 1 export
densityHeat

added 1 export
densityHeatlpp
1.65-3
record
2021-02-05
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2021-02-05
Total releases: 29 / 5 yrs
License: GPL (>= 2) OSI
Minimum R: ≥ 3.5.0
Download size: 342 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("spatstat.linnet")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.18637/jss.v055.i11, 10.18637/jss.v012.i06.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for spatstat.linnet version 3.5-4 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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