{"product_id":"mathematical-theory-of-bayesian-statistics","title":"Mathematical Theory of Bayesian Statistics","description":"Mathematical Theory of Bayesian Statisticsintroduces 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\u003cul\u003e\n\u003cbr\u003e Explains Bayesian inference not subjectively but objectively. \u003cbr\u003e\u003cbr\u003e Provides a mathematical framework for conventional Bayesian theorems.\u003cbr\u003e\u003cbr\u003e Introduces and proves new theorems. \u003cbr\u003e\u003cbr\u003e Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view. \u003cbr\u003e\u003cbr\u003e Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests. \u003cbr\u003e \u003c\/ul\u003eThis book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians.AuthorSumio 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.","brand":"Taylor \u0026 Francis","offers":[{"title":"Default Title","offer_id":44521881731310,"sku":"9780367734817","price":88.0,"currency_code":"AUD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0630\/9612\/7726\/files\/9780367734817.jpg?v=1702061181","url":"https:\/\/bookland.com.au\/products\/mathematical-theory-of-bayesian-statistics","provider":"Book Land AU","version":"1.0","type":"link"}