| 书目名称 | Statistical Analysis of Network Data |
| 副标题 | Methods and Models |
| 编辑 | Eric D. Kolaczyk |
| 视频video | |
| 概述 | Unified presentation of statistical models and methods from across the variety of disciplines engaged in ‘network science’.Balanced presentation of concepts and mathematics.Examples, including extende |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. |
| 出版日期 | Book 2009 |
| 关键词 | Graph; bioinformatics; complex networks; network; network analysis; network modeling; network statistical |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-88146-1 |
| isbn_softcover | 978-1-4419-2776-7 |
| isbn_ebook | 978-0-387-88146-1Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer-Verlag New York 2009 |
发表于 2025-3-21 18:10:03
