Bayesian methods
贝叶斯推断
贝叶斯推断是一种统计范式，其中概率代表信念程度而非长期频率。它将关于参数的先验知识编码到先验分布中，通过贝叶斯定理将该先验与观测数据的似然结合，并生成一个量化更新不确定性的后验分布。这一奠基性定理由托马斯·贝叶斯于1763年死后发表，随后由皮埃尔-西蒙·拉普拉斯在其1812年的《概率分析理论》中系统化。
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来源
- Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418. link ↗
- Laplace, P.-S. (1812). Théorie analytique des probabilités. Courcier, Paris. link ↗
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). Chapman & Hall/CRC. ISBN: 978-1439840955
如何引用本页
ScholarGate. (2026, June 3). Bayesian Statistical Inference. ScholarGate. https://scholargate.app/zh/statistics/bayesian-inference
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