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 flexible 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 flexibility 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 loc...
In recent years permutation testing methods have increased both in number of applications and in sol...
Complex multivariate testing problems are frequently encountered in many scientific disciplines, suc...
We study properties of two resampling scenarios: Conditional Randomisation and Conditional Permutati...
This description of the R package coin is a (slightly) modified version of Hothorn, Hornik, van de W...
The coin package implements a unified approach for conditional inference pro-cedures commonly known ...
Conditioning on the observed data is an important and flexible design principle for statistical test...
Background: For small, skewed, sparse, unbalanced data, or data with lots of ties the exact P values...
Abstract Conditioning on the observed data is an important and flexible design principle for statist...
Conditioning on the observed data is an important and flexible design principle for statistical test...
Conditioning on the observed data is an important and flexible design principle for statistical test...
The R-package jmuOutlier, which contains functions for performing nonparametric statistical analyses...
We propose a general new method, the conditional permutation test, for testing the conditional indep...
The importance and usefulness of nonparametric methods for testing statistical hypotheses has been ...
Complex multivariate testing problems are frequently encountered in many scientific disciplines, suc...
Title: Permutation Tests of Statistical Hypotheses Author: Zdeněk Veselý Department: Department of P...
In recent years permutation testing methods have increased both in number of applications and in sol...
Complex multivariate testing problems are frequently encountered in many scientific disciplines, suc...
We study properties of two resampling scenarios: Conditional Randomisation and Conditional Permutati...
This description of the R package coin is a (slightly) modified version of Hothorn, Hornik, van de W...
The coin package implements a unified approach for conditional inference pro-cedures commonly known ...
Conditioning on the observed data is an important and flexible design principle for statistical test...
Background: For small, skewed, sparse, unbalanced data, or data with lots of ties the exact P values...
Abstract Conditioning on the observed data is an important and flexible design principle for statist...
Conditioning on the observed data is an important and flexible design principle for statistical test...
Conditioning on the observed data is an important and flexible design principle for statistical test...
The R-package jmuOutlier, which contains functions for performing nonparametric statistical analyses...
We propose a general new method, the conditional permutation test, for testing the conditional indep...
The importance and usefulness of nonparametric methods for testing statistical hypotheses has been ...
Complex multivariate testing problems are frequently encountered in many scientific disciplines, suc...
Title: Permutation Tests of Statistical Hypotheses Author: Zdeněk Veselý Department: Department of P...
In recent years permutation testing methods have increased both in number of applications and in sol...
Complex multivariate testing problems are frequently encountered in many scientific disciplines, suc...
We study properties of two resampling scenarios: Conditional Randomisation and Conditional Permutati...