2007, Cambridge series in statistical and probabilistic mathematics, ISBN 0521866561, Volume 20, ix, 212

The theory of random graphs began in the late 1950s in several papers by Erdos and Renyi...

Random graphs | History and criticism | Contemporary Christian music | Christian rock music

Random graphs | History and criticism | Contemporary Christian music | Christian rock music

Book

Social networks, ISSN 0378-8733, 01/2009, Volume 31, Issue 1, pp. 12 - 25

Recent advances in Exponential Random Graph Models (ERGMs), or
p
âˆ—
models, include new specifications that give a much better chance of model convergence for large networks compared with the traditional Markov models...

MCMC MLE | Partial conditional dependence assumption | Exponential random graph ( [formula omitted]) models | Affiliation networks | Exponential random graph (p ) models | Anthropology | Social Sciences | Life Sciences & Biomedicine | Sociology | Science & Technology | Markov processes | Analysis | Models

MCMC MLE | Partial conditional dependence assumption | Exponential random graph ( [formula omitted]) models | Affiliation networks | Exponential random graph (p ) models | Anthropology | Social Sciences | Life Sciences & Biomedicine | Sociology | Science & Technology | Markov processes | Analysis | Models

Journal Article

The Annals of statistics, ISSN 0090-5364, 10/2013, Volume 41, Issue 5, pp. 2428 - 2461

We introduce a method for the theoretical analysis of exponential random graph models...

Statistical graphs | Broken symmetry | Mathematical theorems | Statistical theories | Mathematical constants | Graph theory | Mathematical functions | Mathematics | Modeling | Vertices | Exponential random graph models | Erdos-RÃ©nyi | Parameter estimation | Graph limit | Random graph | Statistics & Probability | Physical Sciences | Science & Technology | Studies | Mathematical models | Statistical analysis | Estimating techniques | exponential random graph models | 60F10 | ErdÅ‘sâ€“RÃ©nyi | 62P25 | graph limit | parameter estimation | 62F10 | 05C80

Statistical graphs | Broken symmetry | Mathematical theorems | Statistical theories | Mathematical constants | Graph theory | Mathematical functions | Mathematics | Modeling | Vertices | Exponential random graph models | Erdos-RÃ©nyi | Parameter estimation | Graph limit | Random graph | Statistics & Probability | Physical Sciences | Science & Technology | Studies | Mathematical models | Statistical analysis | Estimating techniques | exponential random graph models | 60F10 | ErdÅ‘sâ€“RÃ©nyi | 62P25 | graph limit | parameter estimation | 62F10 | 05C80

Journal Article

Social networks, ISSN 0378-8733, 01/2013, Volume 35, Issue 1, pp. 96 - 115

â–º A generalized multilevel network data structure is presented. â–º Directed and nondirected ERGM specifications for two-level networks are proposed. â–º...

Exponential random graph models | Multilevel networks | Anthropology | Social Sciences | Life Sciences & Biomedicine | Sociology | Science & Technology | Humanities and Social Sciences

Exponential random graph models | Multilevel networks | Anthropology | Social Sciences | Life Sciences & Biomedicine | Sociology | Science & Technology | Humanities and Social Sciences

Journal Article

Sociological methodology, ISSN 1467-9531, 06/2016, Volume 36, Issue 1, pp. 99 - 153

The most promising class of statistical models for expressing structural properties of social networks observed at one moment in time is the class of exponential random graph models (ERGMs), also known as p* models...

Datasets | Friendship | Statistical graphs | Triangles | Social networking | New Methods for Specific Situations: Cohort Models, Exponential Graphs, Event Histories, Cluster Studies and Logit Analyses | Mathematical independent variables | Markov models | Parametric models | Modeling | Statistics | DISTRIBUTIONS | RANDOM TRIANGLE MODEL | LOGIT-MODELS | LOGISTIC REGRESSIONS | SOCIAL NETWORKS | COMPLEX NETWORKS | LIKELIHOOD | MARKOV GRAPHS | Monte Carlo method | Models | Algorithms | Social aspects | Analysis | Probability | Social networks | Monte Carlo simulation | Structural models | Statistical analysis | Stochastic models | Graph algorithms | Specifications

Datasets | Friendship | Statistical graphs | Triangles | Social networking | New Methods for Specific Situations: Cohort Models, Exponential Graphs, Event Histories, Cluster Studies and Logit Analyses | Mathematical independent variables | Markov models | Parametric models | Modeling | Statistics | DISTRIBUTIONS | RANDOM TRIANGLE MODEL | LOGIT-MODELS | LOGISTIC REGRESSIONS | SOCIAL NETWORKS | COMPLEX NETWORKS | LIKELIHOOD | MARKOV GRAPHS | Monte Carlo method | Models | Algorithms | Social aspects | Analysis | Probability | Social networks | Monte Carlo simulation | Structural models | Statistical analysis | Stochastic models | Graph algorithms | Specifications

Journal Article

2017, London Mathematical Society lecture note series, ISBN 1108125603, Volume 438, xi, 226 pages

This introduction to random walks on infinite graphs gives particular emphasis to graphs with polynomial volume growth...

Markov processes | Graph theory | Heat equation | Random walks (Mathematics)

Markov processes | Graph theory | Heat equation | Random walks (Mathematics)

Book

Journal of statistical software, ISSN 1548-7660, 2018, Volume 83, Issue 6, pp. 1 - 36

The xergm package is an implementation of extensions to the exponential random graph model (ERGM...

Xergm | Relational data | Network analysis | Btergm | TERGM | Temporal exponential random graph model | relational data | xergm | R | temporal exponential random graph model | btergm | network analysis

Xergm | Relational data | Network analysis | Btergm | TERGM | Temporal exponential random graph model | relational data | xergm | R | temporal exponential random graph model | btergm | network analysis

Journal Article

2010, ISBN 9780199206650, cm.

The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the...

Mathematical and Statistical Physics | Network analysis (Planning) | Social systems | Systems biology | System analysis | Engineering systems | Computer Networks | Generative Models | Social Networks | Graph Theory | Computer Algorithms | Spectral Methods | Network Data | Internet | Biological Networks | Random Graph Models | Social networks | Computer networks | Algorithms

Mathematical and Statistical Physics | Network analysis (Planning) | Social systems | Systems biology | System analysis | Engineering systems | Computer Networks | Generative Models | Social Networks | Graph Theory | Computer Algorithms | Spectral Methods | Network Data | Internet | Biological Networks | Random Graph Models | Social networks | Computer networks | Algorithms

Book

Social networks, ISSN 0378-8733, 01/2011, Volume 33, Issue 1, pp. 41 - 55

Exponential random graph models are extremely difficult models to handle from a statistical viewpoint, since their normalising constant, which depends on model parameters, is available only in very trivial cases...

Exponential random graph models | Markov chain Monte Carlo | Social network analysis

Exponential random graph models | Markov chain Monte Carlo | Social network analysis

Journal Article

The Annals of statistics, ISSN 0090-5364, 04/2013, Volume 41, Issue 2, pp. 508 - 535

.... Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact...

Statistical graphs | Statistical models | Projectibility | Generating function | Statistical theories | Social networking | Statistical mechanics | Parametric models | Statistics | Modeling | Network sampling | Sufficient statistics | Exponential random graph model | Exponential family | Independent increments | Network models | Projective family | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Parameter estimation | Graph theory | Stochastic models | Random variables | Maximum likelihood method | projective family | independent increments | 62M99 | network models | 91D30 | exponential random graph model | sufficient statistics | 60G51 | 62M09 | 62B05 | network sampling

Statistical graphs | Statistical models | Projectibility | Generating function | Statistical theories | Social networking | Statistical mechanics | Parametric models | Statistics | Modeling | Network sampling | Sufficient statistics | Exponential random graph model | Exponential family | Independent increments | Network models | Projective family | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Parameter estimation | Graph theory | Stochastic models | Random variables | Maximum likelihood method | projective family | independent increments | 62M99 | network models | 91D30 | exponential random graph model | sufficient statistics | 60G51 | 62M09 | 62B05 | network sampling

Journal Article

2010, ISBN 9780199206650, cm.

The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the...

Mathematical and Statistical Physics | Network analysis (Planning) | Social systems | Systems biology | System analysis | Engineering systems | Computer Networks | Generative Models | Social Networks | Graph Theory | Computer Algorithms | Spectral Methods | Network Data | Internet | Biological Networks | Random Graph Models | Social networks | Computer networks | Algorithms

Mathematical and Statistical Physics | Network analysis (Planning) | Social systems | Systems biology | System analysis | Engineering systems | Computer Networks | Generative Models | Social Networks | Graph Theory | Computer Algorithms | Spectral Methods | Network Data | Internet | Biological Networks | Random Graph Models | Social networks | Computer networks | Algorithms

Book