401-6228-00L Programming with R for Reproducible Research

Abstract	Deeper understanding of R: Function calls, rather than "commands". Reproducible research and data analysis via Sweave and Rmarkdown. Limits of floating point arithmetic. Understanding how functions work. Environments, packages, namespaces. Closures, i.e., Functions returning functions. Lists and [mc]lapply() for easy parallelization. Performance measurement and improvements.
Objective	Learn to understand R as a (very versatile and flexible) programming language and learn about some of its lower level functionalities which are needed to understand why R works the way it does.
Content	See "Skript": https://github.com/mmaechler/ProgRRR/tree/master/ETH
Lecture notes	Material available from Github https://github.com/mmaechler/ProgRRR/tree/master/ETH (typically will be updated during course)
Literature	Norman Matloff (2011) The Art of R Programming - A tour of statistical software design. no starch press, San Francisco. on stock at Polybuchhandlung (CHF 42.-). More material, notably H.Wickam's "Advanced R" : see my ProgRRR github page.
Prerequisites / Notice	R Knowledge on the same level as after both parts of the ETH lecture 401-6217-00L Using R for Data Analysis and Graphics Link An interest to dig deeper than average R users do. Bring your own laptop with a recent version of R installed