Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Bootstrap paramétrique× | Test par permutation (ou randomisation)× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1993 | 2005 |
| Auteur d'origine≠ | Efron & Tibshirani; Davison & Hinkley | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Type≠ | Resampling-based inference (model-based) | Nonparametric resampling test |
| Source fondatrice≠ | Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317 | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Alias≠ | parametrik bootstrap, model-based bootstrap, parametric resampling | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Apparentées | 5 | 5 |
| Résumé≠ | The parametric bootstrap is a resampling method that estimates standard errors and confidence intervals by drawing repeated samples from a parametric model that has been fitted to the data. Developed in the bootstrap literature of Efron and Tibshirani (1993) and Davison and Hinkley (1997), it replaces analytic derivations for non-normal distributions and complex statistics. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
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