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Titlebook: WAIC and WBIC with R Stan; 100 Exercises for Bu Joe Suzuki Textbook 2023 The Editor(s) (if applicable) and The Author(s), under exclusive l

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发表于 2025-3-21 17:51:27 | 显示全部楼层 |阅读模式
书目名称WAIC and WBIC with R Stan
副标题100 Exercises for Bu
编辑Joe Suzuki
视频video
概述Focuses on widely applicable information criterion (WAIC) & widely applicable Bayesian information criterion (WBIC).Presents 100 carefully selected exercises accompanied by solutions in the main text.
图书封面Titlebook: WAIC and WBIC with R Stan; 100 Exercises for Bu Joe Suzuki Textbook 2023 The Editor(s) (if applicable) and The Author(s), under exclusive l
描述Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. This book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in R and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory..The key features of this indispensable book include:.A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise..100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension..A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once co
出版日期Textbook 2023
关键词Watanabe Bayesian Theory; Statistics; WAIC; Watanabe-Akaike Information Criterion; WBIC; Watanabe Bayesia
版次1
doihttps://doi.org/10.1007/978-981-99-3838-4
isbn_softcover978-981-99-3837-7
isbn_ebook978-981-99-3838-4
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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发表于 2025-3-21 22:28:39 | 显示全部楼层
Introduction to Watanabe Bayesian Theory,finite variance. We derive the relationships between homogeneity, realizability, regularity, and relatively finite variance. Finally, we derive the posterior distribution when the statistical model is an exponential family distribution and its conjugate prior distribution is applie
发表于 2025-3-22 02:55:57 | 显示全部楼层
Mathematical Preparation,metry and related topics, please refer to Chapter 6. Readers who already understand the content of this chapter may skip it as appropriate. At the end of the chapter, we provide the proof of Proposition ., which was postponed in Chapter 1 and can be understood with the preliminary knowledge of this chapter, it can be understood.
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发表于 2025-3-22 11:15:20 | 显示全部楼层
elected exercises accompanied by solutions in the main text.Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-A
发表于 2025-3-22 15:16:34 | 显示全部楼层
,Overview of Watanabe’s Bayes,ibe the full picture of Watanabe’s Bayes Theory. In this chapter, we would like to avoid rigorous discussions and talk in an essay-like manner to grasp the overall picture. From now on, we will write the sets of non-negative integers, real numbers, and complex numbers as ., ., and ., respectively.
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发表于 2025-3-23 00:10:17 | 显示全部楼层
Introduction to Watanabe Bayesian Theory,ion. Next, we define the true distribution . and the statistical model ., and find the set of . that minimizes the Kullback-Leibler (KL) information between them, denoted as .. We then introduce the concepts of homogeneity with respect to ., realizability, and regularity between . and .. The Watanab
发表于 2025-3-23 04:07:09 | 显示全部楼层
Introduction to Watanabe Bayesian Theory,ion. Next, we define the true distribution . and the statistical model ., and find the set of . that minimizes the Kullback-Leibler (KL) information between them, denoted as .. We then introduce the concepts of homogeneity with respect to ., realizability, and regularity between . and .. The Watanab
发表于 2025-3-23 07:54:30 | 显示全部楼层
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