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2012 Moment-Based Estimation of Stochastic Kronecker Graph Parameters
David F. Gleich, Art B. Owen
Internet Math. 8(3): 232-256 (2012).


Stochastic Kronecker graphs supply a parsimonious model for large sparse real-world graphs. They can specify the distribution of a large random graph using only three or four parameters. Those parameters have, however, proved difficult to choose in specific applications. This article looks at method-of-moments estimators that are computationally much simpler than maximum likelihood. The estimators are fast, and in our examples, they typically yield Kronecker parameters with expected feature counts closer to a given graph than we get from KronFit. The improvement is especially prominent for the number of triangles in the graph.


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David F. Gleich. Art B. Owen. "Moment-Based Estimation of Stochastic Kronecker Graph Parameters." Internet Math. 8 (3) 232 - 256, 2012.


Published: 2012
First available in Project Euclid: 21 August 2012

zbMATH: 1258.05111
MathSciNet: MR2967066

Rights: Copyright © 2012 A K Peters, Ltd.


Vol.8 • No. 3 • 2012
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