Introduction
This is an R package that implements functions for working with absorbing Markov chains using theorems described in the book “Finite Markov Chains” by Kemeny and Snell. The design of this package is based on the implementation of these theorems in the framework described by Fletcher et al. in Toward a unified framework for connectivity that disentangles movement and mortality in space and time (Ecology Letters, 2019; DOI: 10.1111/ele.13333), which applies them to spatial ecology. This framework incorporates both resistance and absorption (or mortality) using spatial absorbing Markov chains to provide several short- and long-term predictions for metrics related to connectivity in landscapes. These metrics are listed in Table 1 of Fletcher et al. (2019), as well as the Overview vignette. Despite the ecological context of the package, these functions can be used in any application of absorbing Markov chains.
Installation
It is recommended that users install the samc package via CRAN, where it will be regularly kept up to date.
install.packages("samc")
Citation
Marx, A.J., Wang, C., Sefair, J.A., Acevedo, M.A. and Fletcher, R.J., Jr. (2020), samc: an R package for connectivity modeling with spatial absorbing Markov chains. Ecography, 43: 518-527. doi:10.1111/ecog.04891
Support
Please note that this section is for package specific queries. If you have questions or comments about the related published articles, contact the authors.
Not sure how to do something? Have an error and can’t fix it?
If you have an error, make sure you are using the newest version of the package. Then, check the site’s Troubleshooting page, which is periodically updated with common errors that users encounter. If you still cannot solve your issue, or just have a question about the package, then check out our Gitter community (also accessible via the Gitter badges in the README and home pages).
Found a bug? Have a feature request?
If you’re getting an error or incorrect output, and are sure it is a bug, then report it as an issue in the GitHub repo (after making sure that it hasn’t already been posted). Make sure to include all possible relevant info (operating system, R version, samc version) and a fully reproducible example. Likewise, if you have a feature you’d like to see, submit it to the issue tracker. Keep in mind that my time is limited, so while I do have plans to add new features, I also have other obligations.
