An Introduction To Exponential Random Graph Modeling

Author : Jenine K. Harris
Publisher : SAGE Publications
ISBN 13 : 148332205X
Total Pages : 136 pages
Book Rating : 4.56/5 ( download)

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Download or read book An Introduction to Exponential Random Graph Modeling written by Jenine K. Harris and published by SAGE Publications. This book was released on 2013-12-23 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. An Introduction to Exponential Random Graph Modeling, by Jenine K. Harris, fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.

Author : Dean Lusher
Publisher : Cambridge University Press
ISBN 13 : 0521193567
Total Pages : 361 pages
Book Rating : 4.66/5 ( download)

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Download or read book Exponential Random Graph Models for Social Networks written by Dean Lusher and published by Cambridge University Press. This book was released on 2013 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs).

Author : Jenine K. Harris
Publisher : SAGE Publications
ISBN 13 : 1483303438
Total Pages : 138 pages
Book Rating : 4.37/5 ( download)

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Download or read book An Introduction to Exponential Random Graph Modeling written by Jenine K. Harris and published by SAGE Publications. This book was released on 2013-12-23 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. An Introduction to Exponential Random Graph Modeling, by Jenine K. Harris, fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.

Author : Anna Goldenberg
Publisher : Now Publishers Inc
ISBN 13 : 1601983204
Total Pages : 118 pages
Book Rating : 4.06/5 ( download)

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Download or read book A Survey of Statistical Network Models written by Anna Goldenberg and published by Now Publishers Inc. This book was released on 2010 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.

Author : Skyler J. Cranmer
Publisher : Cambridge University Press
ISBN 13 : 1107158125
Total Pages : 317 pages
Book Rating : 4.22/5 ( download)

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Download or read book Inferential Network Analysis written by Skyler J. Cranmer and published by Cambridge University Press. This book was released on 2020-11-19 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.

Author : Alan Frieze
Publisher : Cambridge University Press
ISBN 13 : 1107118506
Total Pages : 483 pages
Book Rating : 4.08/5 ( download)

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Download or read book Introduction to Random Graphs written by Alan Frieze and published by Cambridge University Press. This book was released on 2016 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.

Author : Remco van der Hofstad
Publisher : Cambridge University Press
ISBN 13 : 110717287X
Total Pages : 341 pages
Book Rating : 4.76/5 ( download)

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Download or read book Random Graphs and Complex Networks written by Remco van der Hofstad and published by Cambridge University Press. This book was released on 2016-12-22 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.

Author : Rolf Sundberg
Publisher : Cambridge University Press
ISBN 13 : 1108476597
Total Pages : 297 pages
Book Rating : 4.91/5 ( download)

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Download or read book Statistical Modelling by Exponential Families written by Rolf Sundberg and published by Cambridge University Press. This book was released on 2019-08-29 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.

Author : Dr. Jens Krause
Publisher : Oxford University Press, USA
ISBN 13 : 0199679053
Total Pages : 279 pages
Book Rating : 4.58/5 ( download)

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Download or read book Animal Social Networks written by Dr. Jens Krause and published by Oxford University Press, USA. This book was released on 2015 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the application of network theory to the social organization of animals.

Author : Martin J. Wainwright
Publisher : Now Publishers Inc
ISBN 13 : 1601981848
Total Pages : 324 pages
Book Rating : 4.44/5 ( download)

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Download or read book Graphical Models, Exponential Families, and Variational Inference written by Martin J. Wainwright and published by Now Publishers Inc. This book was released on 2008 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.