9780521141383-0521141389-Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Structural Analysis in the Social Sciences, Series Number 35)

Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Structural Analysis in the Social Sciences, Series Number 35)

ISBN-13: 9780521141383
ISBN-10: 0521141389
Edition: Illustrated
Author: Dean Lusher, Johan Koskinen, Garry Robins
Publication date: 2012
Publisher: Cambridge University Press
Format: Paperback 360 pages
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Book details

ISBN-13: 9780521141383
ISBN-10: 0521141389
Edition: Illustrated
Author: Dean Lusher, Johan Koskinen, Garry Robins
Publication date: 2012
Publisher: Cambridge University Press
Format: Paperback 360 pages

Summary

Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Structural Analysis in the Social Sciences, Series Number 35) (ISBN-13: 9780521141383 and ISBN-10: 0521141389), written by authors Dean Lusher, Johan Koskinen, Garry Robins, was published by Cambridge University Press in 2012. With an overall rating of 3.9 stars, it's a notable title among other Research (Social Sciences) books. You can easily purchase or rent Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (Structural Analysis in the Social Sciences, Series Number 35) (Paperback) from BooksRun, along with many other new and used Research books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $4.46.

Description

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.

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