Statistical Science

Permutation Methods: A Basis for Exact Inference

Michael D. Ernst

Full-text: Open access

Abstract

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.

Article information

Source
Statist. Sci., Volume 19, Number 4 (2004), 676-685.

Dates
First available in Project Euclid: 18 April 2005

Permanent link to this document
https://projecteuclid.org/euclid.ss/1113832732

Digital Object Identifier
doi:10.1214/088342304000000396

Mathematical Reviews number (MathSciNet)
MR2185589

Zentralblatt MATH identifier
1100.62563

Keywords
Distribution-free Monte Carlo nonparametric permutation tests randomization tests

Citation

Ernst, Michael D. Permutation Methods: A Basis for Exact Inference. Statist. Sci. 19 (2004), no. 4, 676--685. doi:10.1214/088342304000000396. https://projecteuclid.org/euclid.ss/1113832732


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