18 results with keyword: 'methods simulating networks exponential random graph models'
Trying this iterative sampling with spectral clustering algorithm on existing networks have generated simulations with very accurate counts and densities of overall, homophilous,
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With the exception of individual 9 for the 10% thresh- old and individual 22 for the 20% threshold, the posterior predictive distribution indicated a reasonable fit with at two or
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However, the networks generated using only propositions related to distance and cultural homophily are not plausible network reconstructions since they do not reflect the
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“Cycle Census Statistics for Exponential Random Graph Models.”... GLI-Graph
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After fitting the two competing models we computed a Bayes factor using the approach described in Section 3 to compare the model with nodal random effects to the one with
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In order to do this, 100 graphs are simulated from 100 independent realisations taken from the estimated posterior distribution and compared to the observed graph in terms of
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Suppose there are m factories called origins or sources produce aI (i=1,2……,m) units of products which are to be transported to n destinations with bJ (J=1,2,……,n) unity of
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Exponential random graph models were used to represent, understand, and predict pig trade networks structures from different European production systems, with predominantly
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The tool can compute the extended view-factor and extended incident heat fluxes for solar, planetary and albedo contributions using the Monte Carlo Ray Tracing model. The software
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Exponential random graph models were used to represent, understand, and predict pig trade networks structures from different European production systems, with predominantly
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We evaluate and extend a new model for inference with network data, the Exponential Random Graph Model (ERGM), that simultaneously allows both inference on covariates and
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In this section we consider four different random graph ensembles: exponential random graph models, random geometric graphs, Erd˝ os-R´ enyi random graphs conditioned on a large
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We compare the predictions of our models to data for a number of real-world social networks and find that in some cases, the models are in remarkable agreement with the data, whereas
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By adopting a qualitative design using structured interviews with 31 participants and convergence analysis of multiple case studies, the study revealed on site operational
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Finite Element Methods • Finite element methods take the benefits of the spectral transform method with the locality principal of finite-volume methods.. • Can be thought of as
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