Zobrazeno 1 - 10
of 351
pro vyhledávání: '"Robins, Garry"'
Publikováno v:
In Social Networks October 2024 79:187-197
Social science research increasingly benefits from statistical methods for understanding the structured nature of social life, including for social network data. However, the application of statistical network models within large-scale community rese
Externí odkaz:
http://arxiv.org/abs/2002.00849
Publikováno v:
PLoS ONE (2020) 15(1): e0227804
Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. However the computational difficulty of ERGM parameter estimation has limited the practical application of this class of models to rel
Externí odkaz:
http://arxiv.org/abs/1904.08063
Autor:
Robins, Garry, Lusher, Dean, Broccatelli, Chiara, Bright, David, Gallagher, Colin, Karkavandi, Maedeh Aboutalebi, Matous, Petr, Coutinho, James, Wang, Peng, Koskinen, Johan, Roden, Bopha, Sadewo, Giovanni Radhitio Putra
Publikováno v:
In Social Networks January 2023 72:108-120
Publikováno v:
Scientific Reports | (2018) 8:11509 https://www.nature.com/articles/s41598-018-29725-8
A major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macro-structural properties observed in actual networks. This statistical approach becomes incre
Externí odkaz:
http://arxiv.org/abs/1802.10311
Autor:
Aboutalebi Karkavandi, Maedeh *, Wang, Peng, Lusher, Dean, Bastian, Brock, McKenzie, Vicki, Robins, Garry
Publikováno v:
In Social Networks January 2022 68:330-345
Publikováno v:
In Social Networks January 2022 68:264-278
Akademický článek
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We study spatial embeddings of random graphs in which nodes are randomly distributed in geographical space. We let the edge probability between any two nodes to be dependent on the spatial distance between them and demonstrate that this model capture
Externí odkaz:
http://arxiv.org/abs/physics/0505128
Publikováno v:
In Social Networks July 2018 54:168-178