Regression modelRegression / GLM
贝叶斯广义线性模型
贝叶斯广义线性模型（Bayesian GLM）通过对回归系数设置先验分布，并利用贝叶斯定理通过数据进行更新，从而扩展了经典的GLM框架。这会产生参数的完整后验分布，而不是单一的点估计，从而能够对任何指数族结果进行更丰富的量化不确定性以及原则性地纳入先验知识。
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Method map
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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
- McCullagh, P., & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman & Hall. ISBN: 978-0412317606
如何引用本页
ScholarGate. (2026, June 3). Bayesian Generalized Linear Model. ScholarGate. https://scholargate.app/zh/statistics/bayesian-generalized-linear-model
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.
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