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Testing Goodness of Fit of Random Graph Models
Department of Probability Theory and Statistics, Eötvös Loránd University, Budapest, 1053, Hungary
Alfréd Rényi Mathematical Institute of the Hungarian Academy of Sciences, Budapest, 1053, Hungary
Department of Mathematics, Rutgers University, New Brunswick, NJ 08901, USA
Statistics Program, University of Delaware, Newark, DE 19716, USA
* Author to whom correspondence should be addressed.
Received: 7 May 2012; in revised form: 8 November 2012 / Accepted: 30 November 2012 / Published: 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
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Cite This Article
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.
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.
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.