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Open AccessArticle

Testing Goodness of Fit of Random Graph Models

1
Department of Probability Theory and Statistics, Eötvös Loránd University, Budapest, 1053, Hungary
2
Alfréd Rényi Mathematical Institute of the Hungarian Academy of Sciences, Budapest, 1053, Hungary
3
Department of Mathematics, Rutgers University, New Brunswick, NJ 08901, USA
4
Statistics Program, University of Delaware, Newark, DE 19716, USA
*
Author to whom correspondence should be addressed.
Algorithms 2012, 5(4), 629-635; https://doi.org/10.3390/a5040629
Received: 7 May 2012 / Revised: 8 November 2012 / Accepted: 30 November 2012 / Published: 6 December 2012
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. View Full-Text
Keywords: random graph; maximum likelihood; rank entropy random graph; maximum likelihood; rank entropy
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.

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