The analysis of network data is an area that is rapidly growing, both within and outside of the discipline of statistics. This review provides a concise summary of methods and models used in the statistical analysis of network data, including the Erdos–Renyi model, the exponential family class of network models, and recently developed latent variable models. Many of the methods and models are illustrated by application to the well-known Zachary karate dataset. Software routines available for implementing methods are emphasized throughout. The aim of this paper is to provide a review with enough detail about many common classes of network models to whet the appetite and to point the way to further reading.Science Foundation Irelan
The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of sta...
Exponential Family Random Graph Models (ERGM) are increasingly used in the study of social networks....
Statistical models for social networks as dependent variables must represent the typical network dep...
The analysis of network data is an area that is rapidly growing, both within and outside of the disc...
We begin with a graph (or a directed graph), a single set of nodes N, and a set of lines or arcs L. ...
Network Analysis is a set of statistical and mathematical techniques for the study of relational dat...
International audienceThis book is a general introduction to the statistical analysis of networks, a...
Covers the foundations common to the statistical analysis of network data across the disciplines. Th...
The new edition of this book provides an easily accessible introduction to the statistical analysis ...
A brief introduction to statistical models for complete network data is presented. An example is pro...
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Fo...
A brief introduction to statistical models for complete network data is presented. An example is pro...
statnet is a suite of software packages for statistical network analysis. The packages implement rec...
The present work is a collection of articles [133, 134, 135] that, in broad terms, are dedicated to...
Explore the multidisciplinary nature of complex networks through machine learning techniques Statis...
The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of sta...
Exponential Family Random Graph Models (ERGM) are increasingly used in the study of social networks....
Statistical models for social networks as dependent variables must represent the typical network dep...
The analysis of network data is an area that is rapidly growing, both within and outside of the disc...
We begin with a graph (or a directed graph), a single set of nodes N, and a set of lines or arcs L. ...
Network Analysis is a set of statistical and mathematical techniques for the study of relational dat...
International audienceThis book is a general introduction to the statistical analysis of networks, a...
Covers the foundations common to the statistical analysis of network data across the disciplines. Th...
The new edition of this book provides an easily accessible introduction to the statistical analysis ...
A brief introduction to statistical models for complete network data is presented. An example is pro...
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Fo...
A brief introduction to statistical models for complete network data is presented. An example is pro...
statnet is a suite of software packages for statistical network analysis. The packages implement rec...
The present work is a collection of articles [133, 134, 135] that, in broad terms, are dedicated to...
Explore the multidisciplinary nature of complex networks through machine learning techniques Statis...
The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of sta...
Exponential Family Random Graph Models (ERGM) are increasingly used in the study of social networks....
Statistical models for social networks as dependent variables must represent the typical network dep...