Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 148332205X
Category : Social Science
Languages : en
Pages : 138
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. This book 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 is a part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which has helped countless students, instructors, and researchers learn cutting-edge quantitative techniques.
An Introduction to Exponential Random Graph Modeling
Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 148332205X
Category : Social Science
Languages : en
Pages : 138
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. This book 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 is a part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which has helped countless students, instructors, and researchers learn cutting-edge quantitative techniques.
Publisher: SAGE Publications
ISBN: 148332205X
Category : Social Science
Languages : en
Pages : 138
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. This book 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 is a part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which has helped countless students, instructors, and researchers learn cutting-edge quantitative techniques.
An Introduction to Exponential Random Graph Modeling
Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 1483303438
Category : Social Science
Languages : en
Pages : 138
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.
Publisher: SAGE Publications
ISBN: 1483303438
Category : Social Science
Languages : en
Pages : 138
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
Exponential Random Graph Models for Social Networks
Author: Dean Lusher
Publisher: Cambridge University Press
ISBN: 0521193567
Category : Business & Economics
Languages : en
Pages : 361
Book Description
This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs).
Publisher: Cambridge University Press
ISBN: 0521193567
Category : Business & Economics
Languages : en
Pages : 361
Book Description
This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs).
Inferential Network Analysis
Author: Skyler J. Cranmer
Publisher: Cambridge University Press
ISBN: 1107158125
Category : Business & Economics
Languages : en
Pages : 317
Book Description
Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.
Publisher: Cambridge University Press
ISBN: 1107158125
Category : Business & Economics
Languages : en
Pages : 317
Book Description
Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.
A Survey of Statistical Network Models
Author: Anna Goldenberg
Publisher: Now Publishers Inc
ISBN: 1601983204
Category : Computers
Languages : en
Pages : 118
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.
Publisher: Now Publishers Inc
ISBN: 1601983204
Category : Computers
Languages : en
Pages : 118
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.
Animal Social Networks
Author: Dr. Jens Krause
Publisher: Oxford University Press, USA
ISBN: 0199679053
Category : Science
Languages : en
Pages : 279
Book Description
This book demonstrates the application of network theory to the social organization of animals.
Publisher: Oxford University Press, USA
ISBN: 0199679053
Category : Science
Languages : en
Pages : 279
Book Description
This book demonstrates the application of network theory to the social organization of animals.
Random Graphs and Complex Networks
Author: Remco van der Hofstad
Publisher: Cambridge University Press
ISBN: 110717287X
Category : Computers
Languages : en
Pages : 341
Book Description
This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.
Publisher: Cambridge University Press
ISBN: 110717287X
Category : Computers
Languages : en
Pages : 341
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
Author: Rolf Sundberg
Publisher: Cambridge University Press
ISBN: 1108476597
Category : Business & Economics
Languages : en
Pages : 297
Book Description
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.
Publisher: Cambridge University Press
ISBN: 1108476597
Category : Business & Economics
Languages : en
Pages : 297
Book Description
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.
Introduction to Random Graphs
Author: Alan Frieze
Publisher: Cambridge University Press
ISBN: 1107118506
Category : Mathematics
Languages : en
Pages : 483
Book Description
The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.
Publisher: Cambridge University Press
ISBN: 1107118506
Category : Mathematics
Languages : en
Pages : 483
Book Description
The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.