coin: A Computational Framework for Conditional Inference

The coin package implements a unified approach for conditional inference procedures commonly known as permutation tests. The theoretical basis of design and implementation is the unified framework for permutation tests given by Strasser and Weber (1999). For a very flexible formulation of multivariate linear statistics, Strasser and Weber (1999) derived the conditional expectation and covariance of the conditional (permutation) distribution as well as the multivariate limiting distribution. For a more detailed overview see Hothorn et al. (2006). Conditional counterparts of a large amount of classical (unconditional) test procedures for continuous, categorical and censored data are part of this framework, for example the Cochran-Mantel-Haenszel test for independence in general contingency tables, linear association tests for ordered categorical data, linear rank tests and multivariate permutation tests. The conceptual framework of permutation tests by Strasser andWeber (1999) for arbitrary problems is available via the generic independence_test. Because convenience functions for the most prominent problems are available, users will