Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Оцінювання методом ресемплінгу «ковзний ніж» (Jackknife Resampling Estimation)× | Тест з перестановки (рандомізації)× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина≠ | Hypothesis test | Regression model |
| Рік появи≠ | 1956 | 2005 |
| Автор методу≠ | 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 |
| Основоположне джерело≠ | 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 |
| Інші назви≠ | delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Пов'язані≠ | 3 | 5 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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