| 书目名称 | Generalized Linear Models With Examples in R | | 编辑 | Peter K. Dunn,Gordon K.‘Smyth | | 视频video | | | 概述 | This book eases students into GLMs and motivates the need for GLMs by starting with regression..A practical working knowledge of good applied statistical practice is developed through the use of these | | 丛书名称 | Springer Texts in Statistics | | 图书封面 |  | | 描述 | .This textbook presents an introduction togeneralized linear models, complete with real-world data sets andpractice problems, making it applicable for both beginning and advancedstudents of applied statistics. Generalized linear models (GLMs) arepowerful tools in applied statistics that extend the ideas of multiplelinear regression and analysis of variance to include response variablesthat are not normally distributed. As such, GLMs can model a widevariety of data types including counts, proportions, and binary outcomesor positive quantities..The book is designed with the student in mind, making it suitable for self-study or a structured course. Beginning with an introduction to linear regression, the book also devotes time to advanced topics not typically included in introductory textbooks. It features chapter introductions and summaries, clear examples, and many practice problems, all carefully designed to balance theory and practice. The text also provides a working knowledge of applied statistical practice through the extensive use of R, which is integrated into the text. .Other features include: .• Advanced topics such as power variance functions, saddlepoint appro | | 出版日期 | Textbook 2018 | | 关键词 | generalized linear models; linear regression; Tweedie family distribution; Saddlepoint approximation; li | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4419-0118-7 | | isbn_ebook | 978-1-4419-0118-7Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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发表于 2025-3-21 19:03:21
