Bayesian methodsBayesian / computational
缺失数据的贝叶斯推断
缺失数据的贝叶斯推断将未观测值视为未知参数，并将其从后验分布中积分出去。该方法不删除或临时插补不完整记录，而是在明确的缺失数据机制下联合建模观测数据和缺失数据，从而产生完全校准的后验不确定性，诚实地反映数据无法告知我们的信息。
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Method map
The neighbourhood of related methods — select a node to explore.
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来源
- Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860
- 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
如何引用本页
ScholarGate. (2026, June 3). Bayesian Inference with Missing Data. ScholarGate. https://scholargate.app/zh/bayesian/bayesian-inference-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.
- 缺失数据下的近似贝叶斯计算贝叶斯↔ compare
- 含缺失数据的贝叶斯分层模型贝叶斯↔ compare
- Bayesian Regression贝叶斯↔ compare
- Gibbs Sampling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