方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 置换 (随机化) 检验× | Jackknife Resampling× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2005 | 1956 |
| 提出者≠ | Good (2005); Edgington & Onghena (2007); resampling tradition | Quenouille (1956); reviewed by Miller (1974) |
| 类型≠ | Nonparametric resampling test | Resampling / bias and variance estimation |
| 开创性文献≠ | 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 ↗ |
| 别名 | randomization test, exact permutation test, re-randomization test, Permütasyon Testi | leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme |
| 相关 | 5 | 5 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|