On the asymptotic normality of estimating the affine preferential attachment network models with random initial degrees

DOI10.1016/J.SPA.2017.03.008zbMath1491.62080arXiv1603.02625OpenAlexW2963075705MaRDI QIDQ2409003

Fengnan Gao, Aad W. van der Vaart

Publication date: 10 October 2017

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.02625

zbMATH Keywords

asymptotic normalitystatistical inferencecomplex networkspreferential attachment model

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05)

Related Items (5)

Directed hybrid random networks mixing preferential attachment with uniform attachment mechanisms ⋮ Consistency of Hill estimators in a linear preferential attachment model ⋮ How rare are power-law networks really? ⋮ Are extreme value estimation methods useful for network data? ⋮ Inference for the degree distributions of preferential attachment networks with zero-degree nodes

Uses Software

• plfit

Cites Work

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• A preferential attachment model with random initial degrees
• Weak convergence and empirical processes. With applications to statistics
• Emergence of Scaling in Random Networks
• Power-Law Distributions in Empirical Data
• Asymptotic Statistics
• The Structure and Function of Complex Networks
• On random trees
• Convergence of stochastic processes

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