Description

The coin package provides an implementation of a general framework for conditional inference procedures commonly known as permutation tests. The framework was developed by Strasser and Weber (1999) and is based on a multivariate linear statistic and its conditional expectation, covariance and limiting distribution. These results are utilized to construct tests of independence between two sets of variables.

The package does not only provide a flexible implementation of the abstract framework, but also provides a large set of convenience functions implementing well-known as well as lesser-known classical and non-classical test procedures within the framework. Many of the tests presented in prominent text books, such as Hollander and Wolfe (1999) or Agresti (2002), are immediately available or can be implemented without much effort. Examples include 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 of independence between two continuous variables as well as tests of marginal homogeneity and symmetry. Approximations of the exact null distribution via the limiting distribution or conditional Monte Carlo resampling are available for every test procedure, while the exact null distribution is currently available for univariate two-sample problems only.

The salient parts of the Strasser-Weber framework are elucidated by Hothorn et al. (2006) and a thorough description of the software implementation is given by Hothorn et al. (2008).

Author(s)

This package is authored by
Torsten Hothorn <Torsten.Hothorn@R-project.org>,
Kurt Hornik <Kurt.Hornik@R-project.org>,
Mark A. van de Wiel <Mark.vdWiel@vumc.nl>,
Henric Winell <Henric.Winell@statistics.uu.se> and
Achim Zeileis <Achim.Zeileis@R-project.org>.

References

Agresti, A. (2002). Categorical Data Analysis, Second Edition. Hoboken, New Jersey: John Wiley & Sons.

Hollander, M. and Wolfe, D. A. (1999). Nonparametric Statistical Methods, Second Edition. New York: John Wiley & Sons.

Hothorn, T., Hornik, K., van de Wiel, M. A. and Zeileis, A. (2006). A Lego system for conditional inference. The American Statistician 60(3), 257–263. doi: 10.1198/000313006X118430

Hothorn, T., Hornik, K., van de Wiel, M. A. and Zeileis, A. (2008). Implementing a class of permutation tests: The coin package. Journal of Statistical Software 28(8), 1–23. doi: 10.18637/jss.v028.i08

Strasser, H. and Weber, C. (1999). On the asymptotic theory of permutation statistics. Mathematical Methods of Statistics 8(2), 220–250.

Examples