Exponential Random Graph Models for Social Networks (Paperback)

Dean Lusher

ISBN 10: 0521141389 / ISBN 13: 9780521141383

Published by Cambridge University Press, Cambridge, 2012

About this Item

Paperback. Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results. Provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs), as well as a compendium of ERGM methods and illustrative applications. The reader is given sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521141383

Bibliographic Details

Title: Exponential Random Graph Models for Social ...

Publisher: Cambridge University Press, Cambridge

Publication Date: 2012

Binding: Paperback

Condition: new

About this title

Synopsis:

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal, and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages, and interpret the results.

Book Description:

The integrated chapters of this edited book provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs), as well as a compendium of ERGM methods and illustrative applications. The reader is given sufficient detail to specify ERGMs, fit them to data with any of the available software packages, and interpret the results.