The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

mrds - Mark-Recapture Distance Sampling

What is 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

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 “Packagesfrom Local Zip file” and browse to location of downloaded zip.
• Or, download package source files.
• Finally the current stable version of mrds is available on CRAN, though this may be up to a month out of date due to CRAN policy.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).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.