We list below other resources that augment the material we have presented in this chapter.
- Xie (2014) delves much further into knitr and LaTeX and other document formats supported by knitr.
- Gandrud (2014) delves not only into knitr, LaTeX, R and RStudio, but also the suite of tools available for the professional data scientist, including utilities such as make, git, and shell.
- http://yihui.name/knitr/ is knitr’s home. This includes documentation on knitr (Xie 2022) and useful discussion forums.
- The knitr (Xie 2022) author’s presentation on knitr (Xie 2022) http://yihui.name/slides/2012-knitr-RStudio.html. The presentation provides a basic introduction to knitr (Xie 2022).
- http://bcb.dfci.harvard.edu/~aedin/courses/ReproducibleResearch/ReproducibleResearch.pdf This lecture provides some insights into literate programming in R.
- LaTeX supports many characters and symbols but finding the right incantation is difficult. This web site, http://detexify.kirelabs.org/classify.html, does a great job. Draw the character you want and it will show you how to get it .
Gandrud, Christopher. 2014. Repreoducible Research with R and RStdio. The R Series. CRC Press.
Xie, Yihui. 2014. Dynamic Documents with R and Knitr. The R Series. CRC Press.
———. 2022. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
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