| Statistical Analysis of Network Data: Methods and Models 2009 Edition Contributor(s): Kolaczyk, Eric D. (Author) |
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ISBN: 038788145X ISBN-13: 9780387881454 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: March 2009 Annotation: The emerging field of "network science" is poised to truly take off in the next few years. This book serves as a central statistical reference as this field congeals. |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Social Science | Methodology - Computers | Databases - Data Mining |
| Dewey: 003.015 |
| LCCN: 2009921812 |
| Series: Springer Statistics |
| Physical Information: 0.9" H x 6.4" W x 9.4" (1.75 lbs) 386 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called 'network science. |