000			01139nam a22002057a 4500
005			20240209175729.0
008			240209b |||||||| |||| 00| 0 eng d
020			_a9780367734817
082			_a519.542 _bWAT
100			_aWatanabe, Sumio _914158
245			_aMathematical theory of bayesian statistics
260			_bCRC Press _aBoca Raton _c2018
300			_aix, 319 p.
365			_aGBP _b49.99
520			_aMathematical 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. (https://www.routledge.com/Mathematical-Theory-of-Bayesian-Statistics/Watanabe/p/book/9780367734817)
650			_aBayesian statistical decision theory _915526
650			_aApplied mathematics _915527
650			_aPsychology - Methodology _915528
942			_cBK _2ddc
999			_c5892 _d5892