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Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2007
ISBN 10: 3540731326 ISBN 13: 9783540731320
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Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2007
ISBN 10: 3540731326 ISBN 13: 9783540731320
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of the same title. Network models have a long history. Sociologists and statisticians made major advances in the 1970s and 1980s, culminating in part with a number of substantial databases and the class of exponential random graph models and related methods in the early 1990s. Physicists and computer scientists came to this domain cons- erably later, but they enriched the array of models and approaches and began to tackle much larger networks and more complex forms of data. Our goal in organ- ing the workshop was to encourage a dialog among people coming from di erent disciplinary perspectives and with di erent methods, models, and tools. Both the workshop and the editing of the proceedings was a truly colla- rative e ort on behalf of all six editors, but three in particular deserve special recognition. Anna Goldenberg and Alice Zheng were the driving force behind the entire enterprise and Edo Airoldi assisted on a number of the more important arrangements.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2007, 2007
ISBN 10: 3540731326 ISBN 13: 9783540731320
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of the same title. Network models have a long history. Sociologists and statisticians made major advances in the 1970s and 1980s, culminating in part with a number of substantial databases and the class of exponential random graph models and related methods in the early 1990s. Physicists and computer scientists came to this domain cons- erably later, but they enriched the array of models and approaches and began to tackle much larger networks and more complex forms of data. Our goal in organ- ing the workshop was to encourage a dialog among people coming from di erent disciplinary perspectives and with di erent methods, models, and tools. Both the workshop and the editing of the proceedings was a truly colla- rative e ort on behalf of all six editors, but three in particular deserve special recognition. Anna Goldenberg and Alice Zheng were the driving force behind the entire enterprise and Edo Airoldi assisted on a number of the more important arrangements.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch.
Taschenbuch. Zustand: Neu. Statistical Network Analysis: Models, Issues, and New Directions | ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers | Edoardo M. Airoldi (u. a.) | Taschenbuch | viii | Englisch | 2007 | Springer | EAN 9783540731320 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Paperback. Zustand: Gut. Softcover reprint of hardcover 1st ed. 400 pp. Cover with slight signs of wear and discolored at spine, well preserved inside 344 Sprache: Englisch Gewicht in Gramm: 763.
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In den WarenkorbZustand: Sehr gut. Zustand: Sehr gut | Seiten: 404 | Sprache: Englisch | Produktart: Bücher | 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.
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Taschenbuch. Zustand: Neu. Statistical Analysis of Network Data | Methods and Models | Eric D. Kolaczyk | Taschenbuch | xii | Englisch | 2010 | Springer | EAN 9781441927767 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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In den WarenkorbPaperback. Zustand: Brand New. 394 pages. 9.25x6.25x1.00 inches. In Stock.
Sprache: Englisch
Verlag: Springer New York, Springer US, 2010
ISBN 10: 144192776X ISBN 13: 9781441927767
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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