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.
Publié le : 2004-11-14
Classification:
Distribution-free,
Monte Carlo,
nonparametric,
permutation tests,
randomization tests
@article{1113832732,
author = {Ernst, Michael D.},
title = {Permutation Methods: A Basis for Exact Inference},
journal = {Statist. Sci.},
volume = {19},
number = {1},
year = {2004},
pages = { 676-685},
language = {en},
url = {http://dml.mathdoc.fr/item/1113832732}
}
Ernst, Michael D. Permutation Methods: A Basis for Exact Inference. Statist. Sci., Tome 19 (2004) no. 1, pp. 676-685. http://gdmltest.u-ga.fr/item/1113832732/