Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест перестановок (рандомизация)× | Метод складного ножа (Jackknife Resampling)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2005 | 1956 |
| Автор метода≠ | Good (2005); Edgington & Onghena (2007); resampling tradition | Quenouille (1956); reviewed by Miller (1974) |
| Тип≠ | Nonparametric resampling test | Resampling / bias and variance estimation |
| Основополагающий источник≠ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 | Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗ |
| Другие названия | randomization test, exact permutation test, re-randomization test, Permütasyon Testi | leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability. |
| ScholarGateНабор данных ↗ |
|
|