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Rdistance
View on CRAN: Click
here
Download and install Rdistance package within the R console
Install from CRAN:
install.packages("Rdistance")
Install from Github:
library("remotes")
install_github("cran/Rdistance") Install by package version:
library("remotes")
install_version("Rdistance", "4.5.0") Attach the package and use:
library("Rdistance")
Maintained by
Trent McDonald
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-03-06
Latest Update: 2025-04-10
Description:
Distance-sampling analyses estimate density and
abundance of organisms in ecology when detection probability declines with
increasing distance from the observers. Distance-sampling is popular
in most branches of ecology and especially when
organisms are observed from aerial platforms (e.g., airplane or drone),
surface vessels (e.g., boat or truck), or along walking transects.
Rdistance analyzes data collected on both point and line transects,
estimates overall (study area) and site-level (transect or point)
density, and allows users to specify regression-like formula (similar
to lm or glm) for covariates. A large suite of classical,
parametric detection functions are
included along with some uncommon parametric
functions (e.g., Gamma, negative exponential) and non-parametric
smoothed distance functions. Custom (user-defined) detection functions
can be implemented (see vignette). Measurement unit integrity is
enforced with internal unit conversion when necessary.
The help files and vignettes have been
vetted by multiple authors and tested in workshop
settings.
How to cite:
Trent McDonald (2012). Rdistance: Density and Abundance from Distance-Sampling Surveys. R package version 4.5.0, https://cran.r-project.org/web/packages/Rdistance. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-09-18 04:20), 1.0 (2012-03-06 07:40), 1.1 (2012-12-07 21:17), 1.2.1 (2015-04-01 23:51), 1.2.2 (2015-04-22 23:09), 1.3.2 (2015-07-22 06:07), 2.1.1 (2018-08-14 17:00), 2.1.2 (2018-08-23 18:24), 2.1.3 (2019-01-03 01:10), 3.0.0 (2023-06-13 09:30), 3.1.4 (2025-03-12 00:30), 4.0.3 (2025-03-29 19:30), 4.0.5 (2025-04-10 19:20), 4.1.1 (2025-12-03 19:30), 4.3.0 (2026-01-10 01:40), 4.3.1 (2026-02-11 09:40), 4.4.0 (2026-04-22 19:50), 4.4.2 (2026-05-09 23:20), 4.4.3 (2026-05-14 15:50)
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