Distance: Distance Sampling Detection Function and Abundance Estimation

A simple way of fitting detection functions to distance sampling data for both line and point transects. Adjustment term selection, left and right truncation as well as monotonicity constraints and binning are supported. Abundance and density estimates can also be calculated (via a Horvitz-Thompson-like estimator) if survey area information is provided. See Miller et al. (2019) <doi:10.18637/jss.v089.i01> for more information on methods and <https://examples.distancesampling.org/> for example analyses.

Version: 1.0.9
Depends: R (≥ 3.5.0), mrds (≥ 2.3.0)
Imports: dplyr, methods, rlang
Suggests: covr, progress, parallel, doParallel, doRNG, foreach, activity, testthat, optimx, readxl
Published: 2023-12-21
Author: David Lawrence Miller, T.J. Clark-Wolf
Maintainer: Laura Marshall <lhm at st-andrews.ac.uk>
BugReports: https://github.com/DistanceDevelopment/Distance/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/DistanceDevelopment/Distance/
NeedsCompilation: no
Language: en-GB
Citation: Distance citation info
Materials: NEWS
In views: Environmetrics
CRAN checks: Distance results

Documentation:

Reference manual: Distance.pdf

Downloads:

Package source: Distance_1.0.9.tar.gz
Windows binaries: r-devel: Distance_1.0.9.zip, r-release: Distance_1.0.9.zip, r-oldrel: Distance_1.0.9.zip
macOS binaries: r-release (arm64): Distance_1.0.9.tgz, r-oldrel (arm64): Distance_1.0.9.tgz, r-release (x86_64): Distance_1.0.9.tgz
Old sources: Distance archive

Reverse dependencies:

Reverse imports: dsims, FORTLS
Reverse suggests: dsm

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