Distance R packages
We have created a suite of R packages that allow design, analysis and simulation of distance sampling data. Some of these packages are used in the Distance for Windows software, but you can also access them directly from R. This page links to resources for downloading and using the distance sampling R packages, including vignettes showing example analyses.
You can download R from the R project website.
A list of available packages is given below. Links to “CRAN” are stable versions of the package, uploaded to the Comprehensive R Archive Network, “github” links are to development versions and are recommended for advanced users only, “wiki” and “readme” links are to online additional documentation.
mrds- fits detection functions to point and line transect distance sampling survey data (for both single and double observer surveys). Abundance can be estimated using Horvitz-Thompson-type estimators. CRAN, github.
Distance- a simpler interface to
mrdsfor single observer distance sampling surveys. CRAN, github, wiki, feature comparison.
dsm- fits density surface models to spatially-referenced distance sampling data. Count data are corrected using detection function models fitted using
Distance. Spatial models are constructed using generalized additive models. CRAN, github, wiki.
dsmextra- a toolkit for quantifying and visualising extrapolation in density surface models. github, readme.
dsims- a package for simulating distance sampling surveys (this new package replaces the now retired DSsim, this vignette gives an example of the small changes required to convert to the new syntax). CRAN, github.
mads- deals with unidentified sightings, covariate uncertainty and model uncertainty in Distance sampling. CRAN, github.
Wondering how to get started with the distance sampling R packages? We recommend our paper in the Journal of Statistical Software for getting started with
We also have a page dedicated to example analyses. Examples were generated from the
.Rmd files . Data files are also supplied so you can duplicate the analyses (if they are not included in packages). The examples site referenced above contains many of the vignettes formerly shown on this page, plus many more examples.
Migrating data and analyses from
Distance for Windows to
Analysis of distance sampling data can be performed either in the
Distance for Windows graphical user interface, or with the
R packages described on this page. An
readdst is under development for reading
Distance for Windows project files into
R for subsequent analysis in
R. The package was written as a testing tool to compare results produced by the
R routines against results produced by
Distance for Windows. However, as we demonstrate in the following vignette,
readdst can be used to migrate some
Distance for Windows projects for analysis in
R (limitations of
readdst are shown in the vignette).