The method of moments and degree distributions for network models

Mathematics – Statistics Theory

Scientific paper

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Published in at http://dx.doi.org/10.1214/11-AOS904 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of

Scientific paper

10.1214/11-AOS904

Probability models on graphs are becoming increasingly important in many applications, but statistical tools for fitting such models are not yet well developed. Here we propose a general method of moments approach that can be used to fit a large class of probability models through empirical counts of certain patterns in a graph. We establish some general asymptotic properties of empirical graph moments and prove consistency of the estimates as the graph size grows for all ranges of the average degree including $\Omega(1)$. Additional results are obtained for the important special case of degree distributions.

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