Bayesian Data Analysis in Ecology with R and Stan
Why this book?
In 2015, we wrote a statistics book for Master/PhD level Bayesian data analyses in ecology (Korner-Nievergelt et al. 2015). You can order it here. People seemed to like it (e.g. (Harju 2016)). Since then, two parallel processes happen. First, we learn more and we become more confident in what we do, or what we do not, and why we do what we do. Second, several really clever people develop software that broaden the spectrum of ecological models that now easily can be applied by ecologists used to work with R. With this e-book, we open the possibility to add new or substantially revised material. In most of the time, it should be in a state that it can be printed and used together with the book as handout for our stats courses.
About this book
We do not copy text from the book into the e-book. Therefore, we refer to the book (Korner-Nievergelt et al. 2015) for reading about the basic theory on doing Bayesian data analyses using linear models. However, Chapters 1 to 17 of this dynamic e-book correspond to the book chapters. In each chapter, we may provide updated R-codes and/or additional material. The following chapters contain completely new material that we think may be useful for ecologists.
While we show the R-code behind most of the analyses, we sometimes choose not to show all the code in the html version of the book. This is particularly the case for some of the illustrations. An intrested reader can always consult the public GitHub repository with the rmarkdown-files that were used to generate the book.
How to contribute?
It is open so that everybody with a GitHub account can make comments and suggestions for improvement. Readers can contribute in two ways. One way is to add an issue. The second way is to contribute content directly through the edit button at the top of the page (i.e. a symbol showing a pencil in a square). That button is linked to the rmarkdown source file of each page. You can correct typos or add new text and then submit a GitHub pull request. We try to respond to you as quickly as possible. We are looking forward to your contribution!
We thank Yihui Xie for providing bookdown which makes it much fun to write open books such as ours.