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A large number of biological, physical, and social systems contain complex networks. Knowledge about how these networks operate is critical for advancing a more general understanding of network behavior. To this end, each of these disciplines has created different kinds of statistical theory for inference on network data. To help stimulate further progress in the field of statistical inference on network data, the NRC sponsored a workshop that brought together researchers who are dealing with network data in different contexts. This book - which is available on CD only - contains the text of the 18 workshop presentations. The presentations focused on five major areas of research: network models, dynamic networks, data and measurement on networks, robustness and fragility of networks, and visualization and scalability of networks.

Suggested Citation

National Research Council. 2007. Proceedings of a Workshop on Statistics on Networks (CD-ROM). Washington, DC: The National Academies Press. https://doi.org/10.17226/12083.

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Publication Info

470 pages |  8.5 x 11 | 

ISBNs: 
  • CD-ROM:  978-0-309-10105-9
  • Ebook:  978-0-309-17882-2
DOI: https://doi.org/10.17226/12083
Chapters skim
Front Matter i-x
Keynote Address, Day 1 Network Complexity and Robustness--John Doyle, California Institute of Technology 1-61
Neurons, Networks, and Noise: An Introduction--Nancy Kopell, Boston University 62-73
Mixing Patterns and Community Structure in Networks--Mark Newman, University of Michigan and Santa Fe Institute 74-119
Dynamic Networks--Embedded Networked Sensing (Redux?)--Deborah Estrin, University of California at Los Angeles 120-168
Dynamic Network Analysis in Counterterrorism Research--Kathleen Carley, Carnegie Mellon University 169-187
Data and Measurement--Current Developments in a Cortically Controlled Brain-Machine Interface--Nicho Hatsopoulos, University of Chicago 188-206
Some Implications of Path-Based Sampling on the Internet--Eric D. Kolaczyk, Boston University 207-225
Network Data and Models--Martina Morris, University of Washington 226-253
The State of the Art in Social Network Analysis--Stephen P. Borgatti, Boston College 254-269
Keynote Address, Day 2--Variability, Homeostasis per Contents and Compensation in Rhythmic Motor Networks--Eve Marder, Brandeis University 270-291
Dynamics and Resilience of Blood Flow in Cortical Microvessels--David Kleinfeld, University of California at San Diego 292-316
Robustness and Fragility--Jean M. Carlson, University of California at Santa Barbara 317-342
Stability and Degeneracy of Network Models--Mark S. Handcock, University of Washington 343-374
Visualization and Scalability--Characterizing Brain Networks with Granger Causality--Mingzhou Ding, University of Florida 375-395
Visualization and Variation: Tracking Complex Networks Across Time and Space--Jon Kleinberg, Cornell University 396-424
Dependency Networks for Relational Data--David Jensen, University of Massachusetts 425-449
Appendix A Workshop Agenda and List of Attendees 450-454
Appendix B Biographical Sketches of Workshop Speakers 455-460

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