Bayesian methodsBayesian / computational
含缺失数据的贝叶斯分层模型
含缺失数据的贝叶斯分层模型将未观测值视为额外的未知数，并与所有模型参数一起从后验分布中进行采样。分层的嵌套结构跨组借用信息，而贝叶斯框架则自然地将缺失带来的不确定性传播到每一个估计和预测中。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
- Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley. ISBN: 978-0471183860
如何引用本页
ScholarGate. (2026, June 3). Bayesian Hierarchical Model with Missing Data Imputation. ScholarGate. https://scholargate.app/zh/bayesian/bayesian-hierarchical-model-with-missing-data
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.
- 缺失数据的贝叶斯推断贝叶斯↔ compare
- 带缺失数据的吉布斯抽样贝叶斯↔ compare
- 分层贝叶斯推断贝叶斯↔ compare
- 缺失数据下的MCMC贝叶斯↔ compare
- 多层贝叶斯推断贝叶斯↔ compare