Regression modelRegression / GLM
贝叶斯概率模型
贝叶斯概率模型是一种二元回归方法，它在贝叶斯框架内使用正态累积分布函数（概率链接）来模拟二元结果的概率。它为回归系数分配先验分布，并用观测数据更新它们，从而得到完整的后验分布，而不是单一的点估计。Albert-Chib数据增强算法通过吉布斯采样使后验采样在计算上更有效率。
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来源
- Albert, J. H., & Chib, S. (1993). Bayesian analysis of binary and polychotomous response data. Journal of the American Statistical Association, 88(422), 669-679. DOI: 10.1080/01621459.1993.10476321 ↗
- 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 Probit Regression Model. ScholarGate. https://scholargate.app/zh/statistics/bayesian-probit-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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