Statistical Inferences by Gaussian Markov Random Fields on Complex Networks
Kazuyuki Tanaka, Takafumi Usui, Muneki Yasuda · 2008
Gaussian Markov random fields are applied to many statistical inferences. Probabilistic models of statistical inferences are constructed in the concept of Bayesian statistics and have some network structures. In the present paper, we analyze the statistical performance of the statistical inferences in Gaussian Markov random fields on some complex networks including scale free networks. We discuss efficiency of scale free networks for statistical inferences of Gauss Markov random fields.