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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
Resources
Lecture Notes
Material available from Githubhttps://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.