Bayesian Modeling

数学函数Markdown写法：

1. https://www.cnblogs.com/fr-ruiyang/p/11317074.html

2. https://blog.csdn.net/qq_35451572/article/details/80303228

3. https://blog.csdn.net/weixin_45459911/article/details/106711996 \hat{\beta}

关于笔记，因为平时上数学lecture的习惯，我习惯于和他人一样，边阅读，边记笔记，但这样很不专注。

理解数学，和摘抄重点，这两者无法同时兼顾，但又生怕错过任何一点。

先理解，再摘抄重点，看似是一件更加专注且高效的行为，但实际上要花去更多的时间。

这样的行为对我本身不利，但这是有意义的。

与其看数学公式，看这些符号如何摆，摆在哪里，这些其实毫无意义，

不如去理解其中抽象的概念，数学家其实也只是把符号随便乱摆，这样看起来方便一些罢了，

如果不理解概念是不可能会做题的，哪怕背下来也是如此，题目只是为了帮助理解概念。

布里斯托大学：Bayesian Modelling 和《贝叶斯统计》

Program

• Chapter 1: Introduction -〉《贝叶斯统计》第一章

• Chapter 2: Decision theory and Bayesian inference -》《贝叶斯统计》4-5章

• Chapter 3: From prior information to prior distribution-》《贝叶斯统计》4-5章

• Chapter 4: Hypothesis testing and credible sets-》《贝叶斯统计》第二章

• Chapter 5: Introduction to Markov chain Monte Carlo methods-》《贝叶斯统计》第七章

• Chapter 6: Bayesian networks-〉未知

• Chapter 7: Hierarchical models-》怀疑在3.5“多层先验”

• Chapter 8: Bayesian asymptotics-〉

• Chapter 9: Model Choice

References

• Chapter 2:

– Chapters 2 and 4 of Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to computational implementation. Springer Science & Business Media.

• Chapter 3:

– Chapter 3 of Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to

computational implementation. Springer Science & Business Media.

• Chapter 4:

– Chapter 5 of Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to

computational implementation. Springer Science & Business Media.

• Chapter 5:

– Chapters 6 and 7 of Robert, C., & Casella, G. (2013). Monte Carlo statistical methods.

Springer Science & Business Media.

– Chapter 1 of Norris, J. R. (1998). Markov chains (No. 2). Cambridge university press.

• Chapter 6:

– Ruggeri, F., Faltin, F., & Kenett, R. (2007). Bayesian networks. Encyclopedia of Statistics in

Quality And Reliability.

• Chapter 7:

– Chapter 10 of Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to

computational implementation. Springer Science & Business Media.

– Chapter 10 of Lunn, D., Jackson, C., Best, N., Spiegelhalter, D., & Thomas, A. (2012). The

BUGS book: A practical introduction to Bayesian analysis. Chapman and Hall/CRC.

• Chapter 8:

– Kleijn, B. J. K., & Van der Vaart, A. W. (2012). The Bernstein-von-Mises theorem under

misspecification. Electronic Journal of Statistics, 6, 354-381.

– Chapter 1 of Ghosh J.K.,& Raamoorthi (2003). Bayesian Nonparamterics. Springer Series in

Statistics.

• Chapter 9:

– Chapter 7 of Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to

computational implementation. Springer Science & Business Media.