This textbook covers the following topics:
- Bayesian Inference
- Representation of Prior Information
- Bayesian Inference in Basic Problems
- Inference by Monte Carlo Methods
- Model Assessment
- Markov Chain Monte Carlo Methods
- Model Selection and Trans-dimensional MCMC
- Methods Based on Analytic Approximations
- Software
Overall the content is very good. It’s a very math heavy book and assumes the reader knows a lot about prior statistics. It took me a longer time to read since I took the time to research anything I didn’t previously know. I would’ve loved to see the author explore python rather than R. That being said, there’s plenty information out their to draw analogies between python and the R portion of this textbook
