Looking for textbooks and/or resources to get familiar with Bayesian decision making. I have the book, Statistical Rethinking, by Richard McElreath and I've found this to be a really great resource for understanding Bayesian statistics. However, the book was written by an anthropologist, so the text is primarily concerned with parameter estimation for the sake of parameter estimation. There is never an objective function by which a decision needs to be made.
For my purposes, I work as an analyst in the product/ads space. I frequently need to estimate parameters but also make decisions therein. I'm aware of algorithms such as UCB, Bayesian Optimization, etc. However, I'm not looking for a single algorithm or subset of algorithms to optimize decisions but rather a resource that covers the core philosophy behind and Bayesian decision solution/algorithm/implementation.
To answer this question, please do as many of the following as possible:
- Reference textbooks about Bayesian decision making (preferably oriented around python,
R is okay, too)
- Reference other materials covering the topic
- Summarize the most salient philosophical components of Bayesian decision making