Conditional Inference Procedures in a Permutation Test Framework The `coin' package implements a general framework for conditional inference procedures, commonly known as permutation tests, theoretically derived by Strasser & Weber (1999). The conditional expectation and covariance for a broad class of multivariate linear statistics as well as the corresponding multivariate limiting distribution was derived by Strasser & Weber (1999). These results are utilized to construct tests for independence between two sets of variables. Beside a general implementation of the abstract framework the package offers a rather huge set of convenience functions implementing well known classical as well as less prominent classical and non-classical test procedures in a conditional inference framework. Examples are linear rank statistics for the two- and K-sample location and scale problem against ordered and unordered alternatives including post-hoc tests for arbitrary contrasts, tests of independence for contingency tables, two- and K-sample tests for censored data, tests for independence of two continuous variables as well as tests for marginal homogeneity and symmetry. Conditional counterparts of most of the classical procedures given in famous text books like Hollander & Wolfe (1999) or Agresti (2002) can be implemented as part of the general framework without much effort. Approximations of the exact null distribution via the limiting distribution and conditional Monte-Carlo procedures are available for every test while the exact null distribution is currently available for two-sample problems only. Inference problems can be specified by a traditional formula based interface. Support for data available as `exprSet' objects in a BioC environment is implemented as well. The theoretical framework is sketched in the vignette and we refer to `vignette("coin")' for further details. Comments, suggestions, bug-reports etc. are more than welcome! Best, Torsten, Kurt, Mark and Achim ______________________________________________________________________ _______ Package: coin Title: Conditional Inference Procedures in a Permutation Test Framework Date: $Date: 2005/06/02 14:55:45 $ Version: 0.2-11 Author: Torsten Hothorn and Kurt Hornik, with contributions by Mark van de Wiel and Achim Zeileis Maintainer: Torsten Hothorn <torsten.hothorn@r-project.org> Description: Conditional inference procedures for the general independence problem including two-sample, K-sample, correlation, censored, ordered and multivariate problems. Depends: R (>= 2.0.0), methods, survival, mvtnorm Suggests: multcomp SaveImage: yes LazyData: yes License: GPL