方法对比
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| 自助法模拟× | 置换 (随机化) 检验× | |
|---|---|---|
| 领域≠ | 仿真 | 统计学 |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 1979 | 2005 |
| 提出者≠ | Bradley Efron | Good (2005); Edgington & Onghena (2007); resampling tradition |
| 类型≠ | Simulation-based nonparametric inference | Nonparametric resampling test |
| 开创性文献≠ | Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| 别名 | bootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling) | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| 相关 | 5 | 5 |
| 摘要≠ | Bootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly resampling with replacement from the observed data. Because it requires no parametric distributional assumptions, it provides a robust, general-purpose alternative to analytical confidence intervals and parametric hypothesis tests across continuous, ordinal, binary, and count data. | 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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