I created and are maintaining a series of R packages that are available on Github under https://github.com/skranz. Most packages are still in a development state with corresponding quirks and many have too little documentation. But they still can already be used. Here is an excerpt of the packages:

RTutor: Interactive problem sets in R that automatically check the solutions and directly provide feedback. As part of their Bachelor/Master Thesis, students of mine have generated very nice interactive problem sets that replicate interesting economic articles. You find links to existing problem sets and documentation on the Github site (https://github.com/skranz/RTutor). Here is a Guide for writing interactive problem sets as part of a Bachelor or Master Thesis.

StratTourn: Tools for running Axelrod-like game theoretic tournaments in R. (Used in student seminars that combine game theory and simulation)

repgame: Numerically solving discounted infinitely repeated games, in which players are risk neutral and can conduct voluntary monetary transfers in each round. It implements the algorithms developed in "Infinitely repeated games with public monitoring and monetary transfers" (JET, 2012) by Susanne Goldlücke and me.

• Here is an older Tutorial: Interactively Solving Repeated Games (Please use the newer installation instruction on Github. For technical reasons, getting again R running within Lyx, it is not trivial for me to update the tutorial).

RMaxima: An R interface to the computer algebra system Maxima (tested on windows only)

LyxMaxima: Using the computer algebra system Maxima from Lyx. Allows computation with your Latex formulas.

restorepoint: Easier debugging in R using restore points instead of break points. The tutorial explains this approachin detail.

stringtools: Toolbox to manipulate strings. Main feature: allows to find and replace strings within nested ( ) blocks, which cannot be generally done with regular expressions.

sktools: Collection of helper function used in my courses, including e.g. functions  to easily analyse AMPL and GMPL models in R.