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lacunaritycovariance

1.1-9

Gliding Box Lacunarity and Other Metrics for 2D Random Closed Sets

0packages depend
3.1Kdownloads / year
93.5%test coverage
13/13checks pass

Overview

About
Maintained by Kassel Liam HingeeFirst published 2019-07-2411 releasesCRAN page ↗GitHub ↗

Functions for estimating the gliding box lacunarity (GBL), covariance, and pair-correlation of a random closed set (RACS) in 2D from a binary coverage map (e.g. presence-absence land cover maps). Contains a number of newly-developed covariance-based estimators of GBL (Hingee et al., 2019) doi:10.1007/s13253-019-00351-9 and balanced estimators, proposed by Picka (2000) http://www.jstor.org/stable/1428408, for covariance, centred covariance, and pair-correlation. Also contains methods for estimating contagion-like properties of RACS and simulating 2D Boolean models. Binary coverage maps are usually represented as raster images with pixel values of TRUE, FALSE or NA, with NA representing unobserved pixels. A demo for extracting such a binary map from a geospatial data format is provided. Binary maps may also be represented using polygonal sets as the foreground, however for most computations such maps are converted into raster images. The package is based on research conducted during the author's PhD studies.

Install

Health

CRAN checks
13OK
Slowest check: 4.6 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.38
93.5%
Coverage · measured lines
100%
Documentation · exports
5
Dependencies · direct
Check history
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 280 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
99%
Return-value docs
100%
References docs
70%

Downloads

3.1K
CRAN downloads in the past year
Rank #13,596 · ~8/day · ~258/mo
Daily download trend is not available in this view yet.
23030 days
77890 days
3.1K1 year
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Repository

Repository
2Stars
2Forks
1Open issues
0Open PRs
0Releases
1,341Commits
8Contributors
1,341 commits · Last activity 2025-09-01

Stars over time

2020-02-21 · 12026-07-07 · 2

Repository practices

Upstream repositoryBeta

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

Checks run against github.com/kasselhingee/lacunaritycovariance on 2026-07-19.

Continuous integration (1)
GitHub Actions
CRAN release process (1)
cran-comments.md
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)
Depends (1)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Listed in earlier versions (1)
no longer listed · 1.1-9
Package Timeline

11 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.1-9Latest
    2025-08-29 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 1.1-7
    2023-11-02 · diff ↗
  • 1.1-6
    2023-11-01 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • 1.1-5
    2023-02-08 · diff ↗
  • 1.1-4
    2022-11-22 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • 1.1-3
    2022-02-15 · diff ↗
  • 1.1-2
    2021-11-07 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • 1.1-1
    2021-03-24 · diff ↗
  • 1.1-0
    2020-09-07 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
Show 3 earlier events
  • 1.0-13
    2020-01-31 · diff ↗
  • 1.0-8
    2019-07-24
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2019-07-24
Total releases
11 / 7 yrs
License
GPL (>= 2) OSI
Download size
300 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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