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lacunaritycovariance  

Gliding Box Lacunarity and Other Metrics for 2D Random Closed Sets
View on CRAN: Click here


Download and install lacunaritycovariance package within the R console
Install from CRAN:
install.packages("lacunaritycovariance")

Install from Github:
library("remotes")
install_github("cran/lacunaritycovariance")

Install by package version:
library("remotes")
install_version("lacunaritycovariance", "1.1-9")



Attach the package and use:
library("lacunaritycovariance")
Maintained by
Kassel Liam Hingee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-24
Latest Update: 2025-09-03
Description:
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) and balanced estimators, proposed by Picka (2000) , 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.
How to cite:
Kassel Liam Hingee (2019). lacunaritycovariance: Gliding Box Lacunarity and Other Metrics for 2D Random Closed Sets. R package version 1.1-9, https://cran.r-project.org/web/packages/lacunaritycovariance. Accessed 10 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:51), 1.0-8 (2019-07-24 09:50), 1.0-13 (2020-01-31 14:20), 1.1-0 (2020-09-07 15:00), 1.1-1 (2021-03-24 14:30), 1.1-2 (2021-11-07 09:00), 1.1-3 (2022-02-15 11:00), 1.1-4 (2022-11-22 10:10), 1.1-5 (2023-02-08 09:12), 1.1-6 (2023-11-01 06:00), 1.1-7 (2023-11-02 14:10)
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