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.
Myles Hollander & Douglas A. Wolfe (1999). Nonparametric Statistical Methods, 2nd Edition. New York: John Wiley & Sons.
Alan Agresti (2002). Categorical Data Analysis Hoboken, New Jersey: John Wiley & Sons.
Torsten Hothorn, Kurt Hornik, Mark A. van de Wiel & Achim Zeileis (2006). A Lego system for conditional inference, The American Statistician, 60(3), 257--263.
Torsten Hothorn, Kurt Hornik, Mark A. van de Wiel & Achim Zeileis (2008).
Implementing a class of permutation tests: The coin package,
Journal of Statistical Software, 28(8), 1--23.