Bayesian analysis of directed graphs data with applications to social networks

Paramjit S. Gill and Tim B. Swartz

Journal of the Royal Statistical Society Series C, 2004, vol. 53, issue 2, 249-260

Abstract: Summary. A fully Bayesian analysis of directed graphs, with particular emphasis on applica‐ tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.

Date: 2004
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