Bayesian methodsBayesian / computational
鲁棒吉布斯采样
鲁棒吉布斯采样是一种马尔可夫链蒙特卡洛策略，它将逐坐标吉布斯采样器与重尾或抗离群值模型规范相结合——最常见的是学生 t 似然函数——从而使后验推断不被极端观测值所扭曲。它通过数据增强实现鲁棒性：每次观测都接收一个潜在的方差权重，该权重在每次采样扫描中自动降低离群值的影响。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40. DOI: 10.1002/jae.3950080504 ↗
- Chib, S. & Greenberg, E. (1995). Understanding the Metropolis-Hastings algorithm. The American Statistician, 49(4), 327–335. DOI: 10.1080/00031305.1995.10476177 ↗
如何引用本页
ScholarGate. (2026, June 3). Robust Gibbs Sampling. ScholarGate. https://scholargate.app/zh/bayesian/robust-gibbs-sampling
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.
- Bayesian Regression贝叶斯↔ compare
- Gibbs Sampling贝叶斯↔ compare
- 稳健贝叶斯推断贝叶斯↔ compare
- 稳健马尔可夫链蒙特卡洛 (Robust Markov Chain Monte Carlo)贝叶斯↔ compare