aam a22 4500
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211464
190326b 2018 ||||| |||| 00| 0 eng d
9781482238068
519.542
W2M2
Watanabe, Sumio
376910
Mathematical theory of bayesian statistics
CRC Press
2018
New York
ix, 319p.
With 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.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, hyper parameter optimization, and hypothesis tests.This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians.
https://www.crcpress.com/Mathematical-Theory-of-Bayesian-Statistics/Watanabe/p/book/9781482238068
Mathematics
376911
Statistics
376912
Mathematical models
376913
Bayesian statistical decision theory
376914
ddc
BK
0
0
ddc
0
519_000000000000000_542_W2M2
0
NFIC
357675
VSL
VSL
GEN
2019-03-25
5
10.00
Slot 1677 (2 Floor, East Wing)
519.542 W2M2
198809
2019-03-25
12571.00
BK