Why does anyone need another book in Bayesian statistics? It seems that there already exist a lot of resources for those interested in the topic. There are many excellent books covering specific aspects of Bayesian analysis or providing a wide and comprehensive background of the entire field: Berger, Bernardo and Smith, Gamerman and Freitas Lopes, Gelman et al., Robert and Cassella, and many others. Most of these books, though, will assume a certain mathematical and statistical background and would rather fit a reader’s profile of a graduate or advanced graduate level. Out of those aimed at a less sophisticated audiences, we would certainly recommend excellent books of William Bolstad, John Kruschke, and Peter Lee. There also exist some very good books on copulas: comprehensive coverage by Nelsen and Joe, and also more application-related Cherubini et al., Emrechts et al., and some others. However, instead of just referring to these works and returning to our extensive to-do lists, we decided to spend considerable amount of time and effort putting together another book—the book we presently offer to the reader.

The main reason for our endeavor is: we target a very specific audience, which as we believe is not sufficiently serviced yet with Bayesian literature. We communicate with members of this audience routinely in our day-to-day work, and we have not failed to register that just providing them with reading recommendations does not seem to satisfy their needs. ...

Get Introduction to Bayesian Estimation and Copula Models of Dependence now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.