Bayesian methods
贝叶斯线性回归
贝叶斯线性回归是普通线性模型的概率性扩展，通过贝叶斯规则引入，并在Gelman等人（2013）的现代计算工作流程中得到形式化。它不为每个系数返回单一的点估计，而是将用户指定的先验分布与观测数据的似然性相结合，生成所有参数的完整后验分布，并从中推导出可信区间和后验预测分布。
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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
如何引用本页
ScholarGate. (2026, June 1). Bayesian Linear Regression. ScholarGate. https://scholargate.app/zh/bayesian/bayesian-linear-regression
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.
- 贝叶斯方差分析 (Bayesian ANOVA)贝叶斯↔ compare
- Bayesian Regression贝叶斯↔ compare
- 马尔可夫链蒙特卡洛 (MCMC)贝叶斯↔ compare
- 普通最小二乘法 (OLS) 回归计量经济学↔ compare