Bayesian Analysis of Directed Graphs Data with Applications to Social Networks
A fully Bayesian analysis of directed graphs, with particular emphasis on applications 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...
Veröffentlicht in: | Journal of the Royal Statistical Society. Series C (Applied Statistics). - Blackwell Publishers. - 53(2004), 2, Seite 249-260 |
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Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2004
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Zugriff auf das übergeordnete Werk: | Journal of the Royal Statistical Society. Series C (Applied Statistics) |
Schlagworte: | Bayesian Analysis Markov Chain Monte Carlo Methods Social Network Models Statistical Graph Theory WinBUGS Applied sciences Mathematics Behavioral sciences Information science |
Zusammenfassung: | A fully Bayesian analysis of directed graphs, with particular emphasis on applications 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. |
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ISSN: | 14679876 |