eBook - ePub

Mathematical Theory of Bayesian Statistics

Name: Mathematical Theory of Bayesian Statistics
ISBN: 9781315355696

Sumio Watanabe,

320 pages
English
ePUB (mobile friendly)
Available on iOS & Android

eBook - ePub

Mathematical Theory of Bayesian Statistics

Sumio Watanabe,

About this book

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 at Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics.

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Yes, you can access Mathematical Theory of Bayesian Statistics by Sumio Watanabe in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.