The Bayesian Choice
From Decision-Theoretic Foundations to Computational Implementation
2nd ed.
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Publication
2007 - Springer, New York, USA
Language
English
Word Count
144,250 words, Guess
Page Count
577 pages
Physical Format
Hardcover
Identifiers
- Internet Archivebayesianchoicefr00robe_046
- Internet Archivebayesianchoicefr00robe
- Internet Archivebayesianchoicefr00robe_947
- ISBN-100387715983
- ISBN-139780387715988
and 7 more
- Google6oQ4s8Pq9pYC
- LibraryThing4561493
- Goodreads47218676
- Library of Congress Control Number2007926596
- OCLC Control Number961034820
- OCLC Control Number255965262
- Open LibraryOL9425514M
Classifications
- DDC519.5/42
Description
A graduate-level textbook that introduces Bayesian statistics and decision theory. It covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, Bayesian model choice, hierarchical and empirical Bayes modeling, Monte Carlo integration including Gibbs sampling, and other MCMC techniques. It was awarded the 2004 DeGroot Prize by the International Society for Bayesian Analysis (ISBA) for setting "a new standard for modern textbooks dealing with Bayesian methods, especially those using MCMC techniques, and that it is a worthy successor to DeGroot's and Berger's earlier texts". ([source][1]) [1]: https://www.springer.com/us/book/9780387952314
Excerpt
The main purpose of statistical theory is to derive from observations of a random phenomenon an inference about the probability distribution underlying this phenomenon.
Description
A graduate-level textbook that introduces Bayesian statistics and decision theory. It covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, Bayesian model choice, hierarchical and empirical Bayes modeling, Monte Carlo integration including Gibbs sampling, and other MCMC techniques. It was awarded the 2004 DeGroot Prize by the International Society for Bayesian Analysis (ISBA) for setting "a new standard for modern textbooks dealing with Bayesian methods, especially those using MCMC techniques, and that it is a worthy successor to DeGroot's and Berger's earlier texts". source: https://www.springer.com/us/book/9780387952314
Subjects
Topics
Series Statement
- Springer Texts in Statistics
Other Editions
- The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation
Show 2 more editions
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