Many basic questions in the social network literature center on the distribution of aggregate structural properties within and across populations of networks. Such questions are of increasing ...

Observational data, although readily available, is sensitive to biases such as confounding by indication. Structure learning algorithms for Bayesian Networks (BNs) can be used to discover the ...

Paramjit S. Gill, Tim B. Swartz, Bayesian Analysis of Directed Graphs Data with Applications to Social Networks, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 53, No. 2 ...

The course is a hands-on introduction and development of the analysis of Bayesian models with using JAGS, stan and R-INLA with focus on data sets and application. The main topics will be Bayesian ...

The node-splitting method was used to examine local inconsistency between direct, indirect and network estimates, and statistical inconsistency was considered when p≤0.05. 36 If significant ...

GRENOBLE, France – Dec. 7, 2023 – A team comprising CEA-Leti, CEA-List and two CNRS laboratories has published a paper in Nature Communications presenting what the authors said is the first complete ...

An international research team led by scientists from Osaka Metropolitan University has developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques ...