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Permanent link (DOI): https://doi.org/10.7939/R3JC78

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A simulation-based approach to assess the goodness of fit of Exponential Random Graph Models Open Access

Descriptions

Other title
Subject/Keyword
Social Networks
Goodness of fit
Exponential Random Graph Models
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Li, Yin
Supervisor and department
Keumhee Carriere Chough (Mathematical and Statistical Sciences)
Examining committee member and department
Peter Hooper (Mathematical and Statistical Sciences)
Sentil Senthilselvan (Public Health)
Department
Department of Mathematical and Statistical Sciences
Specialization

Date accepted
2010-10-01T17:38:36Z
Graduation date
2010-11
Degree
Master of Science
Degree level
Master's
Abstract
Exponential Random Graph Models (ERGMs) have been developed for fitting social network data on both static and dynamic levels. However, the lack of large sample asymptotic properties makes it inadequate in assessing the goodness-of-fit of these ERGMs. Simulation-based goodness-of-fit plots were proposed by Hunter et al (2006), comparing the structured statistics of observed network with those of corresponding simulated networks. In this research, we propose an improved approach to assess the goodness of fit of ERGMs. Our method is shown to improve the existing graphical techniques. We also propose a simulation based test statistic with which the model comparison can be easily achieved.
Language
English
DOI
doi:10.7939/R3JC78
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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