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Mathematical theory of Bayesian stat...
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Watanabe, Sumio.
Mathematical theory of Bayesian statistics
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Mathematical theory of Bayesian statistics/ Sumio Watanabe.
Author:
Watanabe, Sumio.
Published:
Boca Raton, FL :CRC Press, : c2018.,
Description:
1 online resource (ix, 319 p.) :ill. :
Notes:
"A Chapman & Hall book."
Subject:
Bayesian statistical decision theory. -
Online resource:
https://www.taylorfrancis.com/books/9781315373010
ISBN:
9781315373010
Mathematical theory of Bayesian statistics
Watanabe, Sumio.
Mathematical theory of Bayesian statistics
[electronic resource] /Sumio Watanabe. - 1st ed. - Boca Raton, FL :CRC Press,c2018. - 1 online resource (ix, 319 p.) :ill.
"A Chapman & Hall book."
Includes bibliographical references and index.
"Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior distribution cannot be approximated by any normal distribution. Features Explains Bayesian inference not subjectively but objectively. Provides a mathematical framework for conventional Bayesian theorems. Introduces and proves new theorems. Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view. Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests. This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians. Author Sumio Watanabe is a professor of Department of Mathematical and Computing Science in Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics."--Provided by publisher.
ISBN: 9781315373010
Standard No.: 10.1201/9781315373010doiSubjects--Topical Terms:
527671
Bayesian statistical decision theory.
LC Class. No.: QA279.5 / .W38 2018
Dewey Class. No.: 519.542
Mathematical theory of Bayesian statistics
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Mathematical theory of Bayesian statistics
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[electronic resource] /
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Sumio Watanabe.
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1st ed.
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Boca Raton, FL :
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CRC Press,
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c2018.
300
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1 online resource (ix, 319 p.) :
$b
ill.
500
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"A Chapman & Hall book."
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$a
Includes bibliographical references and index.
520
$a
"Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior distribution cannot be approximated by any normal distribution. Features Explains Bayesian inference not subjectively but objectively. Provides a mathematical framework for conventional Bayesian theorems. Introduces and proves new theorems. Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view. Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests. This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians. Author Sumio Watanabe is a professor of Department of Mathematical and Computing Science in Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics."--Provided by publisher.
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Description based on print version record.
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Bayesian statistical decision theory.
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527671
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Mathematical statistics.
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https://www.taylorfrancis.com/books/9781315373010
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