Permutation Methods: A Basis for Exact Inference

作者：Michael D. Ernst · 发表于：Statistical Science · 年份：2004 · DOI：10.1214/088342304000000396 · 被引用次数：826 · 研究领域：Bayesian Modeling and Causal Inference、Machine Learning and Algorithms、Bayesian Methods and Mixture Models

The use of permutation methods for exact inference dates back to Fisher in 1935. Since then, the practicality of such methods has increased steadily with computing power. They can now easily be employed in many situations without concern for computing difficulties. We discuss the reasoning behind these methods and describe situations when they are exact and distribution-free. We illustrate their use in several examples.