Large deviations for empirical measures of generalized random graphs

DOI10.1080/03610926.2020.1779748OpenAlexW3036605488MaRDI QIDQ5081017

Qun Liu, Zhi Shan Dong

Publication date: 1 June 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1779748

zbMATH Keywords

empirical measureslarge deviation principlesgeneralized random graphs

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Scale-free graphs with many edges

Cites Work

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• Central limit type theorems in the generalized random graphs with random vertex weights
• Large deviation principles for empirical measures of colored random graphs
• Generating simple random graphs with prescribed degree distribution
• Large deviations in generalized random graphs with node weights
• Large deviations for mixtures
• Connected components in random graphs with given expected degree sequences
• Limit laws in the generalized random graphs with random vertex weights
• Random Graphs and Complex Networks
• The Evolution of Random Graphs
• The phase transition in inhomogeneous random graphs
• On a conditionally Poissonian graph process

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