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Bayesian Social Science Statistics : Volume 2: Getting Productive.
・ISBN 978-1-009-59844-6 2025 hard GB£ 55.00
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-1-009-34098-4
| 著者・編者 | Gill, Jeff / Bao, Le, |
|---|---|
| シリーズ | Elements in Quantitative and Computational Methods for the Social Sciences |
| 出版社 | (Cambridge University Press, UK) |
| ページ数 | 116 pp. |
| 言語 | ENG |
| ニュース番号 | ＜M25-16473＞ |
解説
This Element introduces the basics of Bayesian regression modeling using modern computational tools. This Element only assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level of Gill and Bao (2024). Some matrix algebra knowledge is assumed but the authors walk carefully through the necessary structures at the start of this Element. At the end of the process readers will fully understand how Bayesian regression models are developed and estimated, including linear and nonlinear versions. The sections cover theoretical principles and real-world applications in order to provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in R and Python is provided throughout.