Implementing a Class of Permutation Tests: The coin Package

• Main Authors: Zeileis, Achim, Wiel, Mark A. van de, Hornik, Kurt, Hothorn, Torsten
• Format: Others
• Language: en
• Published: American Statistical Association 2008
• Subjects: conditional inference / exact distribution / conditional Monte Carlo / categorical data analysis / R
• Online Access: http://epub.wu.ac.at/4004/1/class.pdf

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 exible 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 exibility of the underlying theory and conditional 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 special 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. (authors' abstract)