A.: Implementing a class of permutation tests: The coin package

This description of the R package coin is a (slightly) modified version of Hothorn, Hornik, van de Wiel, and Zeileis (2008a) published in the Journal of Statistical Software. The R package coin implements a unified approach to permutation tests providing a huge class of independence tests for nominal, ordered, numeric, and censored data as well as multivariate data at mixed scales. Based on a rich and flexible conceptual framework that embeds different permutation test procedures into a common theory, a computational framework is established in coin that likewise embeds the corresponding R functionality in a common S4 class structure with associated generic functions. As a consequence, the computational tools in coin inherit the flexibility of the underlying theory and con-ditional inference functions for important special cases can be set up easily. Conditional versions of classical tests—such as tests for location and scale problems in two or more samples, independence in two- or three-way contingency tables, or association problems for censored, ordered categorical or multivariate data—can easily be implemented as spe-cial cases using this computational toolbox by choosing appropriate transformations of the observations. The paper gives a detailed exposition of both the internal structure of the package and the provided user interfaces along with examples on how to extend the implemented functionality