Randomization tests
Permutation, Parametric, and Bootstrap Tests of Hypotheses (Springer Series in Statistics)
Permutation, Parametric, and Bootstrap Tests of Hypotheses (Springer Series in Statistics)
Resampling Methods: A Practical Guide to Data Analysis
Resampling Methods: A Practical Guide to Data Analysis
An Introduction to Bootstrap Methods with Applications to R
An Introduction to Bootstrap Methods with Applications to R
| Hi-index | 0.00 |
Resampling methods are statistical procedures that reuse the sample data for the purpose of statistical inference. However, they do not require parametric assumptions that may be difficult to verify in practice. This focus article describes four resampling techniques, the bootstrap, the jackknife, cross-validation, and permutation tests. Another method, subsampling, is mentioned with two references but is not covered in any detail. These resampling methods and the history of their development are outlined in this paper. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.