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Mathematical Theory of Bayesian Statistics

Af: Sumio Watanabe Engelsk Paperback
SPAR
kr 79

Mathematical Theory of Bayesian Statistics

Af: Sumio Watanabe Engelsk Paperback

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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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.



Produktdetaljer
Sprog: Engelsk
Sider: 332
ISBN-13: 9780367734817
Indbinding: Paperback
Udgave:
ISBN-10: 0367734818
Udg. Dato: 18 dec 2020
Længde: 28mm
Bredde: 154mm
Højde: 233mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 18 dec 2020
Forfatter(e): Sumio Watanabe
Forfatter(e) Sumio Watanabe


Kategori Psykologisk teori og skoleretninger


Sprog Engelsk


Indbinding Paperback


Sider 332


Udgave


Længde 28mm


Bredde 154mm


Højde 233mm


Udg. Dato 18 dec 2020


Oplagsdato 18 dec 2020

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