Bayesian Core by Jean-Michel Marin
A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)

No critic rating

Waiting for minimum critic reviews

See Reader Rating

Synopsis

This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. While R programs are provided on the book website and R hints are given in the computational sections of the book, The Bayesian Core requires no knowledge of the R language and it can be read and used with any other programming language. The Bayesian Core can be used as a textbook at both undergraduate and graduate levels, as exemplified by courses given at Université Paris Dauphine (France), University of Canterbury (New Zealand), and University of British Columbia (Canada). It serves as a unique textbook for a service course for scientists aiming at analyzing data the Bayesian way as well as an introductory course on Bayesian statistics. The prerequisites for the book are a basic knowledge of probability theory and of statistics. Methodological and data-based exercises are included within the main text and students are expected to solve them as they read the book. Those exercises can obviously serve as assignments, as was done in the above courses. Datasets, R codes and course slides all are available on the book website.
 

About Jean-Michel Marin

See more books from this Author
Robert, CREST-INSEE, Paris, France.
 
Published May 26, 2007 by Springer New York. 258 pages
Genres: Computers & Technology, Nature & Wildlife, Professional & Technical, Science & Math. Non-fiction

Reader Rating for Bayesian Core
44%

An aggregated and normalized score based on 6 user ratings from iDreamBooks & iTunes


Rate this book!

Add Review
×