*RATest*: A collection of permutation tests (Joint with Ignacio Sarmiento Barbieri)

**Description:** A collection of randomization tests, data sets and examples. This version considers three main testing problems. The first one concerns with the general testing problem of comparisons of parameters between 2 or more populations, e.g. comparison of means, medians or variances, as well as parameters that depend on the joint
distribution of populations as in *Chung and Romano (2013)*. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in *Canay and Kamat (2018)*. Finally, it provides the practitioner with an effortless implementation of a permutation test based on the martingale decomposition of the empirical process for the goodness-of-fit testing problem with an estimated nuisance parameter. An application of this testing problem is the one of testing for heterogeneous treatment effects in a randomized control trial.

**Vignettes and Extra Documentation:** Additional information regarding the testing problem of comparison of parameters can be found here. A vignette which illustrates the use of the package in the RDD testing problem is also available here, and
this really cool tutorial on R-Bloggers written by Ignacio Sarmiento Barbieri ,the co-creator of RATest.