An Introduction to Exponential Random Graph Modeling

An Introduction to Exponential Random Graph Modeling PDF Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 148332205X
Category : Social Science
Languages : en
Pages : 136

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Book Description
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.

An Introduction to Exponential Random Graph Modeling

An Introduction to Exponential Random Graph Modeling PDF Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 148332205X
Category : Social Science
Languages : en
Pages : 136

Get Book

Book Description
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.

An Introduction to Exponential Random Graph Modeling

An Introduction to Exponential Random Graph Modeling PDF Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 1483303438
Category : Social Science
Languages : en
Pages : 138

Get Book

Book Description
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.

Exponential Random Graph Models for Social Networks

Exponential Random Graph Models for Social Networks PDF Author: Dean Lusher
Publisher: Cambridge University Press
ISBN: 0521193567
Category : Business & Economics
Languages : en
Pages : 361

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Book Description
This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs).

Inferential Network Analysis

Inferential Network Analysis PDF Author: Skyler J. Cranmer
Publisher: Cambridge University Press
ISBN: 1107158125
Category : Business & Economics
Languages : en
Pages : 317

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Book Description
Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.

Introduction to Random Graphs

Introduction to Random Graphs PDF Author: Alan Frieze
Publisher: Cambridge University Press
ISBN: 1107118506
Category : Mathematics
Languages : en
Pages : 483

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Book Description
The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.

A Survey of Statistical Network Models

A Survey of Statistical Network Models PDF Author: Anna Goldenberg
Publisher: Now Publishers Inc
ISBN: 1601983204
Category : Computers
Languages : en
Pages : 118

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Book Description
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.

Random Graphs and Complex Networks

Random Graphs and Complex Networks PDF Author: Remco van der Hofstad
Publisher: Cambridge University Press
ISBN: 110717287X
Category : Computers
Languages : en
Pages : 341

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Book Description
This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.

Statistical Modelling by Exponential Families

Statistical Modelling by Exponential Families PDF Author: Rolf Sundberg
Publisher: Cambridge University Press
ISBN: 1108476597
Category : Business & Economics
Languages : en
Pages : 297

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Book Description
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.

Large Deviations for Random Graphs

Large Deviations for Random Graphs PDF Author: Sourav Chatterjee
Publisher: Springer
ISBN: 3319658166
Category : Mathematics
Languages : en
Pages : 170

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Book Description
This book addresses the emerging body of literature on the study of rare events in random graphs and networks. For example, what does a random graph look like if by chance it has far more triangles than expected? Until recently, probability theory offered no tools to help answer such questions. Important advances have been made in the last few years, employing tools from the newly developed theory of graph limits. This work represents the first book-length treatment of this area, while also exploring the related area of exponential random graphs. All required results from analysis, combinatorics, graph theory and classical large deviations theory are developed from scratch, making the text self-contained and doing away with the need to look up external references. Further, the book is written in a format and style that are accessible for beginning graduate students in mathematics and statistics.

Random Graph Dynamics

Random Graph Dynamics PDF Author: Rick Durrett
Publisher: Cambridge University Press
ISBN: 1139460889
Category : Mathematics
Languages : en
Pages : 203

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Book Description
The theory of random graphs began in the late 1950s in several papers by Erdos and Renyi. In the late twentieth century, the notion of six degrees of separation, meaning that any two people on the planet can be connected by a short chain of people who know each other, inspired Strogatz and Watts to define the small world random graph in which each site is connected to k close neighbors, but also has long-range connections. At a similar time, it was observed in human social and sexual networks and on the Internet that the number of neighbors of an individual or computer has a power law distribution. This inspired Barabasi and Albert to define the preferential attachment model, which has these properties. These two papers have led to an explosion of research. The purpose of this book is to use a wide variety of mathematical argument to obtain insights into the properties of these graphs. A unique feature is the interest in the dynamics of process taking place on the graph in addition to their geometric properties, such as connectedness and diameter.