Bayesian methodsBayesian / computational
分层自助法模拟
分层自助法模拟是一种重采样技术，专为具有嵌套或聚类结构的数据设计——例如，学校内的学生、医院内的患者、受试者内的重复测量。它通过按层次结构中的每个级别依次重采样来保留数据的自然分组，从而生成一个采样分布，该分布正确反映了组间和组内的变异性。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Davison, A. C. & Hinkley, D. V. (1997). Bootstrap Methods and their Application. Cambridge University Press. ISBN: 978-0521574716
- Cameron, A. C., Gelbach, J. B. & Miller, D. L. (2008). Bootstrap-based improvements for inference with clustered errors. Review of Economics and Statistics, 90(3), 414-427. DOI: 10.1162/rest.90.3.414 ↗
如何引用本页
ScholarGate. (2026, June 3). Hierarchical Bootstrap Simulation. ScholarGate. https://scholargate.app/zh/bayesian/hierarchical-bootstrap-simulation
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Gibbs Sampling贝叶斯↔ compare
- 分层贝叶斯推断贝叶斯↔ compare
- 卡尔曼滤波器贝叶斯↔ compare
- 多层自助法模拟贝叶斯↔ compare
- 顺序蒙特卡洛贝叶斯↔ compare