mads: Multi-Analysis Distance Sampling

Performs distance sampling analyses on a number of species at once and can account for unidentified sightings, model uncertainty and covariate uncertainty. Unidentified sightings refer to sightings which cannot be allocated to a single species but may instead be allocated to a group of species. The abundance of each unidentified group is estimated and then prorated to the species estimates. Model uncertainty should be incorporated when multiple models give equally good fit to the data but lead to large differences in estimated density / abundance. Covariate uncertainty should be incorporated when covariates cannot be measured accurately, for example this is often the case for group size in marine mammal surveys. Variance estimation for these methods is via a non parametric bootstrap. The methods implemented are described in Gerodette T. and Forcada J. (2005) <doi:10.3354/meps291001> Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean.

Version: 0.1.6
Depends: R (≥ 3.5.0), mrds, stats
Suggests: testthat
Published: 2020-05-27
Author: Laura Marshall
Maintainer: Laura Marshall <lhm at st-and.ac.uk>
BugReports: https://github.com/DistanceDevelopment/mads/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: mads results

Downloads:

Reference manual: mads.pdf
Package source: mads_0.1.6.tar.gz
Windows binaries: r-devel: mads_0.1.6.zip, r-release: mads_0.1.6.zip, r-oldrel: mads_0.1.6.zip
macOS binaries: r-release (arm64): mads_0.1.6.tgz, r-release (x86_64): mads_0.1.6.tgz, r-oldrel: mads_0.1.6.tgz
Old sources: mads archive

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