Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Оценка методом джекknife× | Тест перестановок (рандомизация)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство≠ | Hypothesis test | Regression model |
| Год появления≠ | 1956 | 2005 |
| Автор метода≠ | Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Тип≠ | Bias and variance estimation | Nonparametric resampling test |
| Основополагающий источник≠ | Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Другие названия≠ | delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Связанные≠ | 3 | 5 |
| Сводка≠ | Jackknife estimation is a classical resampling technique that computes the bias and variance of a statistical estimator by systematically leaving out one observation at a time and re-computing the statistic on each reduced sample. Introduced by Maurice Quenouille in 1956 for bias correction and extended by John Tukey in 1958 who coined the name, it is the historical predecessor of the bootstrap and remains analytically tractable for smooth, differentiable estimators. | 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. |
| ScholarGateНабор данных ↗ |
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