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arXiv · 1202.3307

A central limit theorem in the $β$-model for undirected random graphs with a diverging number of vertices

Ting Yan·Jinfeng Xu
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Abstract

Chatterjee, Diaconis and Sly (2011) recently established the consistency of the maximum likelihood estimate in the $β$-model when the number of vertices goes to infinity. By approximating the inverse of the Fisher information matrix, we obtain its asymptotic normality under mild conditions. Simulation studies and a data example illustrate the theoretical results.

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Ting Yan, Jinfeng Xu. 2013-06-30. A central limit theorem in the $β$-model for undirected random graphs with a diverging number of vertices. https://doi.org/10.1093/biomet%2Fass084

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