Maximum likelihood estimation of parameters in the exponential random graph model

Bachelor thesis (2017)

Authors

D.P. Bosma Electrical Engineering, Mathematics and Computer Science

Contributors

Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2017 Douwe Bosma
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Published Date

24-11-2017

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In this report the method of Markov chain Monte Carlo maximum
likelihood estimation was used to estimate parameters in the Ising model
and the exponential random graph model. The method and the models
where described mathematically and problems that occurred during the
estimation process where discussed. A package that executes the method
was built in programming language Julia and is tested on precision. It
was concluded that the precision is high in most situation and that, in
these situations, the speed of convergence of the estimation can be found
in the results.

Files

BEP_Report_Douwe_Bosma_Maximum... (pdf)
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- Embargo expired in 24-11-2017