| 书目名称 | Regression | | 副标题 | Models, Methods and | | 编辑 | Ludwig Fahrmeir,Thomas Kneib,Brian Marx | | 视频video | | | 概述 | Applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application.Written in textbook style suitable for students, the material is | | 图书封面 |  | | 描述 | The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference. | | 出版日期 | Textbook 20131st edition | | 关键词 | generalized linear models; linear regression; mixed models; semiparametric regression; spatial regressio | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-34333-9 | | isbn_ebook | 978-3-642-34333-9 | | copyright | Springer-Verlag Berlin Heidelberg 2013 |
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发表于 2025-3-21 20:07:07
