Package: mrds 3.0.0
Laura Marshall
mrds: Mark-Recapture Distance Sampling
Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.
Authors:
mrds_3.0.0.tar.gz
mrds_3.0.0.tar.gz(r-4.5-noble)mrds_3.0.0.tar.gz(r-4.4-noble)
mrds_3.0.0.tgz(r-4.4-emscripten)mrds_3.0.0.tgz(r-4.3-emscripten)
mrds.pdf |mrds.html✨
mrds/json (API)
NEWS
| # Install 'mrds' in R: |
| install.packages('mrds', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/distancedevelopment/mrds/issues19 issues
- book.tee.data - Golf tee data used in chapter 6 of Advanced Distance Sampling examples
- lfbcvi - Black-capped vireo mark-recapture distance sampling analysis
- lfgcwa - Golden-cheeked warbler mark-recapture distance sampling analysis
- pronghorn - Pronghorn aerial survey data from Wyoming
- ptdata.distance - Single observer point count data example from Distance
- ptdata.dual - Simulated dual observer point count data
- ptdata.removal - Simulated removal observer point count data
- ptdata.single - Simulated single observer point count data
- stake77 - Wooden stake data from 1977 survey
- stake78 - Wooden stake data from 1978 survey
Last updated 5 months agofrom:55b6b455ee. Checks:2 OK, 1 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 23 2025 |
| R-4.5-linux | NOTE | Mar 23 2025 |
| R-4.4-linux | OK | Mar 23 2025 |
Exports:add_df_covar_lineadd.df.covar.lineassign.parcheck.monocreate.binscreate.ddfobjddfddf.gofDeltaMethoddet.tablesdetfctdhtdht.sep_dist_tablep.dist.tableqqplot.ddfsolvecovvarn
Dependencies:latticeMatrixmgcvnlmenloptrnumDerivoptimxpracmaRsolnptruncnorm
Citation
To cite package ‘mrds’ in publications use:
Laake J, Miller D, Petersma F (2024). mrds: Mark-Recapture Distance Sampling. R package version 3.0.0, https://CRAN.R-project.org/package=mrds.
Corresponding BibTeX entry:
@Manual{,
title = {mrds: Mark-Recapture Distance Sampling},
author = {Jeff Laake and David Miller and Felix Petersma},
year = {2024},
note = {R package version 3.0.0},
url = {https://CRAN.R-project.org/package=mrds},
}
Readme and manuals
mrds - Mark-Recapture Distance Sampling
What is mrds?mrds
This package for R analyzes single or double observer distance sampling data for line or point sampling. It is used in program DISTANCE as one of the analysis engines. Supported double observer configurations include independent, trial and removal. Not all options in mrds are fully supported via DISTANCE.
If you only wish to perform a conventional or multiple covariate distance sampling analysis (CDS/MCDS) (as opposed to a double observer analysis), you may want to try the Distance R package, which has a simplified interface and is available from https://github.com/DistanceDevelopment/Distance.
Getting mrds
mrds
The easiest way to ensure you have the latest version of mrds, is to install using the remotes package:
install.packages("remotes")
then install mrds from github:
library(remotes)
install_github("DistanceDevelopment/mrds")
Otherwise:
- One can download a Windows package binary using the "Releases" tab in github. To install in R, from the R menu, use "Packages\Install from Local Zip file" and browse to location of downloaded zip.
- Or, download package source files.
- Finally the current stable version of
mrdsis available on CRAN, though this may be up to a month out of date due to CRAN policy.
References
The following are references for the methods used in the package.
Burt, M. L., D. L. Borchers, K. J. Jenkins and T. A. Marques. (2014). "Using mark-recapture distance sampling methods on line transect surveys." Methods in Ecology and Evolution 5: 1180-1191.
Buckland, S. T., J. Laake, et al. (2010). "Double observer line transect methods: levels of independence." Biometrics 66: 169-177.
Borchers, D. L., J. L. Laake, et al. (2006). "Accommodating unmodeled heterogeneity in double-observer distance sampling surveys." Biometrics 62(2): 372-378.
Buckland, S. T., D. R. Anderson, et al., Eds. (2004). Advanced distance sampling: estimating abundance of biological populations. Oxford, UK; New York, Oxford University Press. (see chapter 6).
