方法对比
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| 贝叶斯自助法（Bayesian Bootstrap，由 Rubin 提出）× | Bootstrap Inference× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1981 | 1979 |
| 提出者≠ | Rubin (1981); large-sample theory by Lo (1987) | Bradley Efron |
| 类型≠ | Resampling / posterior simulation | Resampling-based inference |
| 开创性文献≠ | Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ |
| 别名≠ | Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı |
| 相关 | 5 | 5 |
| 摘要≠ | The Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated. | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. |
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