1 + 1[1] 21 Introduction
The posterior distribution is obtained from the prior distribution and sampling model via Bayes’ rule:
\[p(\theta \mid y)=\frac{p(y \mid \theta) p(\theta)}{\int_{\Theta} p(y \mid \tilde{\theta}) p(\tilde{\theta}) d \tilde{\theta}}.\]
This is a book created from markdown and executable code.
See Knuth (1984) for additional discussion of literate programming.
1.1 Why Bayesian?
Interesting Article:
Goligher, E.C., Harhay, M.O. (2023). What Is the Point of Bayesian Analysis?, American Journal of Respiratory and Critical Care Medicine, 209, 485–487.