Handbook of Bayesian Variable Selection
暫譯: 貝葉斯變數選擇手冊
Tadesse, Mahlet G., Vannucci, Marina
- 出版商: CRC
- 出版日期: 2021-12-21
- 售價: $6,820
- 貴賓價: 9.5 折 $6,479
- 語言: 英文
- 頁數: 528
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367543761
- ISBN-13: 9780367543761
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相關分類:
機率統計學 Probability-and-statistics
海外代購書籍(需單獨結帳)
相關主題
商品描述
Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed.
The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. The topics covered include spike-and-slab priors, continuous shrinkage priors, Bayes factors, Bayesian model averaging, partitioning methods, as well as variable selection in decision trees and edge selection in graphical models. The handbook targets graduate students and established researchers who seek to understand the latest developments in the field. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions.
Features:
- Provides a comprehensive review of methods and applications of Bayesian variable selection.
- Divided into four parts: Spike-and-Slab Priors; Continuous Shrinkage Priors; Extensions to various Modeling; Other Approaches to Bayesian Variable Selection.
- Covers theoretical and methodological aspects, as well as worked out examples with R code provided in the online supplement.
- Includes contributions by experts in the field.
商品描述(中文翻譯)
貝葉斯變數選擇在過去30年中隨著大型數據集的增長經歷了重大的發展。識別要納入模型的相關變數可以簡化解釋，避免過擬合和多重共線性，並能提供對觀察現象背後機制的見解。當潛在預測變數的數量遠大於樣本大小且可以合理假設稀疏性時，變數選擇尤其重要。
《貝葉斯變數選擇手冊》提供了貝葉斯變數選擇方法的理論、方法論和計算方面的全面回顧。涵蓋的主題包括尖峰與板條先驗（spike-and-slab priors）、連續收縮先驗（continuous shrinkage priors）、貝葉斯因子（Bayes factors）、貝葉斯模型平均（Bayesian model averaging）、分割方法（partitioning methods），以及決策樹中的變數選擇和圖形模型中的邊緣選擇。該手冊的目標讀者是研究生和希望了解該領域最新發展的成熟研究人員。它也為所有有興趣應用現有方法和/或追求方法擴展的人提供了寶貴的參考。
特色：
- 提供貝葉斯變數選擇方法和應用的全面回顧。
- 分為四個部分：尖峰與板條先驗；連續收縮先驗；各種建模的擴展；貝葉斯變數選擇的其他方法。
- 涵蓋理論和方法論方面，以及提供在線補充的R代碼的實例。
- 包含該領域專家的貢獻。
作者簡介
Mahlet Tadesse is Professor and Chair in the Department of Mathematics and Statistics at Georgetown University, USA. Her research over the past two decades has focused on Bayesian modeling for high-dimensional data with an emphasis on variable selection methods and mixture models. She also works on various interdisciplinary projects in genomics and public health. She is a recipient of the Myrto Lefkopoulou Distinguished Lectureship award, an elected member of the International Statistical Institute and an elected fellow of the American Statistical Association.
Marina Vannucci is Noah Harding Professor of Statistics at Rice University, USA. Her research over the past 25 years has focused on the development of methodologies for Bayesian variable selection in linear settings, mixture models and graphical models, and on related computational algorithms. She also has a solid history of scientific collaborations and is particularly interested in applications of Bayesian inference to genomics and neuroscience. She has received an NSF CAREER award and the Mitchell prize by ISBA for her research, and the Zellner Medal by ISBA for exceptional service over an extended period of time with long-lasting impact. She is an elected Member of ISI and RSS and an elected fellow of ASA, IMS, AAAS and ISBA.
作者簡介(中文翻譯)
Mahlet Tadesse 是美國喬治城大學數學與統計系的教授及系主任。她在過去二十年的研究專注於高維數據的貝葉斯建模，特別強調變數選擇方法和混合模型。她還參與了多個跨學科的基因組學和公共衛生項目。她是Myrto Lefkopoulou傑出講座獎的獲得者，並且是國際統計學會的當選會員以及美國統計協會的當選院士。
Marina Vannucci 是美國萊斯大學的Noah Harding統計學教授。她在過去25年的研究專注於線性環境中貝葉斯變數選擇方法的發展、混合模型和圖形模型，以及相關的計算算法。她在科學合作方面有著堅實的歷史，特別對貝葉斯推斷在基因組學和神經科學中的應用感興趣。她因其研究獲得了NSF CAREER獎，並因其卓越的服務和持久的影響力獲得ISBA的Mitchell獎和Zellner獎。她是ISI和RSS的當選會員，以及ASA、IMS、AAAS和ISBA的當選院士。
