TY - GEN
T1 - Statistical inferences by gaussian markov random fields on complex networks
AU - Tanaka, Kazuyuki
AU - Usui, Takafumi
AU - Yasuda, Muneki
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=70449566995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449566995&partnerID=8YFLogxK
U2 - 10.1109/CIMCA.2008.14
DO - 10.1109/CIMCA.2008.14
M3 - Conference contribution
AN - SCOPUS:70449566995
SN - 9780769535142
T3 - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
SP - 214
EP - 219
BT - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
T2 - 2008 International Conference on Computational Intelligence for Modelling Control and Automation, CIMCA 2008
Y2 - 10 December 2008 through 12 December 2008
ER -