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Algorithms 2012, 5(4), 629-635; doi:10.3390/a5040629

Testing Goodness of Fit of Random Graph Models

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Received: 7 May 2012 / Revised: 8 November 2012 / Accepted: 30 November 2012 / Published: 6 December 2012
Download PDF [136 KB, updated 6 December 2012; original version uploaded 6 December 2012]
Abstract: Random graphs are matrices with independent 0–1 elements with probabilities determined by a small number of parameters. One of the oldest models is the Rasch model where the odds are ratios of positive numbers scaling the rows and columns. Later Persi Diaconis with his coworkers rediscovered the model for symmetric matrices and called the model beta. Here we give goodness-of-fit tests for the model and extend the model to a version of the block model introduced by Holland, Laskey and Leinhard.
Keywords: random graph; maximum likelihood; rank entropy random graph; maximum likelihood; rank entropy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Csiszár, V.; Hussami, P.; Komlós, J.; Móri, T.F.; Rejtõ, L.; Tusnády, G. Testing Goodness of Fit of Random Graph Models. Algorithms 2012, 5, 629-635.

AMA Style

Csiszár V, Hussami P, Komlós J, Móri TF, Rejtõ L, Tusnády G. Testing Goodness of Fit of Random Graph Models. Algorithms. 2012; 5(4):629-635.

Chicago/Turabian Style

Csiszár, Villõ; Hussami, Péter; Komlós, János; Móri, Tamás F.; Rejtõ, Lídia; Tusnády, Gábor. 2012. "Testing Goodness of Fit of Random Graph Models." Algorithms 5, no. 4: 629-635.

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