This repository hosts the tutorials for the ipmr workshop from ESA 2021. Tutorials are stored in ipmr_examples/ subfolder. To run with RStudio:
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clone this repository into a folder on your computer.
- The easiest way is to click the green "Code" button in the upper right corner of this page and download a Zip file. Unzip the folder after downloading.
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Open
ipmr_esa.Rproj. -
Open
ipmr_examples/ipmr_tutorial.rmd. -
Click the
Run Documentbutton above the script pane.
To run from the R GUI, follow step 1 from above, then:
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Set your working directory to the path where the unzipped repository is.
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Run
rmarkdown::run("ipmr_examples/ipmr_tutorial.rmd").
In order to get the most out of this tutorial, you will need to be familiar with the regression modeling and when to use different link functions (e.g. Logit, Log). We also assume you are familiar with matrix population models, what a state vector is, and basic analyses like per-capita growth rates and stable state distributions. There are a variety of good publications to familiarize yourself with IPM theory and practice. Merow et al. 2014 is a good start. Though not required for this tutorial, more advanced treatments can be found in Ellner & Rees 2006, Rees & Ellner 2009, and Ellner, Childs, & Rees 2016.
You will also need to install the following R packages:
install.packages(c("DiagrammeR","learnr", "rlang", "MASS"))
This tutorial makes use of the latest version of ipmr. You'll also need either update or install it:
install.packages("ipmr")