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Springer Series in Statistics Ser.: Statistical Analysis of Network Data : Methods and Models by Eric D. Kolaczyk (2009, Hardcover)
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About this product
Product Identifiers
PublisherSpringer New York
ISBN-10038788145X
ISBN-139780387881454
eBay Product ID (ePID)13038295015
Product Key Features
Number of PagesXii, 386 Pages
LanguageEnglish
Publication NameStatistical Analysis of Network Data : Methods and Models
SubjectProbability & Statistics / General, Networking / General, System Theory
Publication Year2009
TypeTextbook
AuthorEric D. Kolaczyk
Subject AreaMathematics, Computers, Science
SeriesSpringer Series in Statistics Ser.
FormatHardcover
Dimensions
Item Weight27.2 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
ReviewsFrom the reviews: "...Accessible and easy to read...strikes a balance between concepts and mathematical detail. ...This book is a superb introduction to a fascinating area." (International Statistical Review, 2010, 78, 1, 134-159) "Many disciplines are nowadays involved in network modeling, but it appears as if a common methodological foundation is lacking. The objective of this book is to provide a first attempt at defining such a common methodological foundation from a statistical point of view. ... The style of the writing is excellent. ... ample references allow quick access to further literature. I can recommend this book to anyone with a serious statistical interest in networks." (Fred van Eeuwijk, VOC Nieuwsbrief, Issue 44, May, 2010) "Any reader interested in networks and wanting a perspective beyond that of any single discipline should acquire this book. ... Researchers will also appreciate the many points in the book where important open problems are identified. The book can also serve readily and flexibly as the main textbook for either a graduate-level seminar course or for an informally organized reading group. ... This book sets itself the challenge of addressing statistics for network science broadly, and in the many ways already noted, it is successful." (Michael Frey, Technometrics, Vol. 54 (1), February, 2012), From the reviews:"…Accessible and easy to read…strikes a balance between concepts and mathematical detail. …This book is a superb introduction to a fascinating area." (International Statistical Review, 2010, 78, 1, 134-159)Many disciplines are nowadays involved in network modeling, but it appears as if a common methodological foundation is lacking. The objective of this book is to provide a first attempt at defining such a common methodological foundation from a statistical point of view. … The style of the writing is excellent. … ample references allow quick access to further literature. I can recommend this book to anyone with a serious statistical interest in networks. (Fred van Eeuwijk, VOC Nieuwsbrief, Issue 44, May, 2010), From the reviews:…Accessible and easy to read…strikes a balance between concepts and mathematical detail. …This book is a superb introduction to a fascinating area. (International Statistical Review, 2010, 78, 1, 134-159) Many disciplines are nowadays involved in network modeling, but it appears as if a common methodological foundation is lacking. The objective of this book is to provide a first attempt at defining such a common methodological foundation from a statistical point of view. … The style of the writing is excellent. … ample references allow quick access to further literature. I can recommend this book to anyone with a serious statistical interest in networks. (Fred van Eeuwijk, VOC Nieuwsbrief, Issue 44, May, 2010)Any reader interested in networks and wanting a perspective beyond that of any single discipline should acquire this book. … Researchers will also appreciate the many points in the book where important open problems are identified. The book can also serve readily and flexibly as the main textbook for either a graduate-level seminar course or for an informally organized reading group. … This book sets itself the challenge of addressing statistics for network science broadly, and in the many ways already noted, it is successful. (Michael Frey, Technometrics, Vol. 54 (1), February, 2012)
Dewey Edition22
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal003.015195
Table Of Contentand Overview.- Preliminaries.- Mapping Networks.- Descriptive Analysis of Network Graph Characteristics.- Sampling and Estimation in Network Graphs.- Models for Network Graphs.- Network Topology Inference.- Modeling and Prediction for Processes on Network Graphs.- Analysis of Network Flow Data.- Graphical Models.
SynopsisThis book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation entails a conscious balance of concepts versus mathematics. In addition, the examples-including extended cases studies-are drawn widely from the literature. This book should be of substantial interest both to statisticians and to anyone else working in the area of 'network science'. The coverage of topics in this book is broad, but unfolds in a systematic manner, moving from descriptive (or exploratory) methods, to sampling, to modeling and inference. Specific topics include network mapping, characterization of network structure, network sampling, and the modeling, inference, and prediction of networks, network processes, and network flows. This book is the first such resource to present material on all of these core topics in one place., This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation balances concepts and mathematics., 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.
LC Classification NumberTK5105.5-5105.9
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