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I will talk about 2 things: how this was shipped and then about the book itself. This book was packed in one of those self seal gold bubble mailers but whoever packed it got the seal on the book itself. I have tried rubbing alcohol and lots of other things to get that seal off to no avail. So I definitely have a complaint on the shipping. As for the book itself, I am very happy it includes sections on nonparametric models. I needed to learn about mixture models and Dirichlet Process Mixtures and this book covers that as well as give lots of examples. Word of warning tho: this book is NOT for beginners. You need to have already gone thru some more basic stats books before reading this one.
The book is thorough but very tedious to work through. It's good to use as a reference manual for Bayesian methods. Needless to say, such sophistication is unnecessary in most common industry applications of data science, but if you are a statistician or an academic practitioner, this is a good handbook to have around, although pricey. A library reference book.
Bayesian Data Analysis is written in a textbook format with problems at the end of each section. Many important concepts are embedded in the problems. An instructor solution manual would be useful for a better understanding of these concepts.
When I saw the advertisement for this book, I noticed that it said "R programs". Since I'm not a mathematician but an end-user, this appealed to me. Then I got the book. This book is more the academic version of Bayesian Data Analysis, with very little on R. Namely, it's not what I expected. The text (at least the chapters that I read) were good, but again, not for an end user.
When will mathematicians learn that not every math book is just for mathematicians?