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2007-06-16

Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)

By Jean-Michel Marin, Christian P. Robert,

Publisher: Springer
Number Of Pages: 258
Publication Date: 2007-02-02
Sales Rank: 50973
ISBN / ASIN: 0387389792
EAN: 9780387389790
Binding: Hardcover
Manufacturer: Springer
Studio: Springer


Book Description:

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 freeduan.com 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.

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2007-6-17 03:31:00

Bayesian Core: A Practical Approach to Computational Bayesian Statistics

Series: Springer Texts in Statistics
Marin, Jean-Michel, Robert, Christian P.
2007, XIV, 258 p., 80 illus., Hardcover
ISBN: 978-0-387-38979-0


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About this textbook
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About this textbook

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. 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.

Written for:
Students
Keywords:
bayesian data analysis
bayesian methodology
bayesian modeling
computational statistics
prior construction
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2008-9-2 07:45:00

哥们,够狠的!但愿不是加了口令的,如果真是那样,------

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2008-9-2 07:53:00
还好不带口令,虽然贵了点,但还应了急需。谢谢了,不过还是想劝劝斑竹降降价吧,20-30也好,50真的很心痛。嗬嗬,
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2008-9-2 08:08:00
太贵了,能否降价?
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2010-7-12 14:46:39
急用,求降价!!!
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