| 书目名称 | Model Averaging | | 编辑 | David Fletcher | | 视频video | | | 概述 | Provides an overview of current model averaging methods, with an emphasis on applications.Compares the frequentist and Bayesian approaches to model averaging.Includes an extensive list of references a | | 丛书名称 | SpringerBriefs in Statistics | | 图书封面 |  | | 描述 | .This book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models.. | | 出版日期 | Book 2018 | | 关键词 | Model averaging; Bayesian Modeling; Frequentist Model Averaging; Mixed models; Posterior model probabili | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-662-58541-2 | | isbn_softcover | 978-3-662-58540-5 | | isbn_ebook | 978-3-662-58541-2Series ISSN 2191-544X Series E-ISSN 2191-5458 | | issn_series | 2191-544X | | copyright | The Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018 |
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发表于 2025-3-21 20:09:22
