Bayesian methodsBayesian / computational
稳健贝叶斯模型平均
稳健贝叶斯模型平均（Robust Bayesian Model Averaging, RBMA）通过用重尾或混合先验（例如，g-先验的混合）以及可选的稳健似然函数替代敏感的共轭先验，扩展了标准贝叶斯模型平均（Bayesian Model Averaging, BMA）。这样，当数据包含异常值、有影响的观测值，或者模型参数的先验可能主导结果时，后验模型概率和平均估计值仍能保持稳定。
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Method map
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来源
- Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401. link ↗
- Ley, E., & Steel, M. F. J. (2012). Mixtures of g-priors for Bayesian model averaging with economic applications. Journal of Econometrics, 171(2), 251–266. link ↗
如何引用本页
ScholarGate. (2026, June 3). Robust Bayesian Model Averaging. ScholarGate. https://scholargate.app/zh/bayesian/robust-bayesian-model-averaging
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.
- 贝叶斯模型平均 (Bayesian Model Averaging, BMA)贝叶斯↔ compare
- Bayesian Regression贝叶斯↔ compare
- 分层贝叶斯推断贝叶斯↔ compare
- 马尔可夫链蒙特卡洛 (MCMC)贝叶斯↔ compare
- 稳健贝叶斯推断贝叶斯↔ compare
- 变分推断贝叶斯↔ compare