Dellaportas, Petros; Giudici, Paolo; Roberts, Gareth Bayesian inference for nondecomposable graphical Gaussian models. (English) Zbl 1192.62090 Sankhyā 65, No. 1, 43-55 (2003). Summary: We propose a method to calculate the posterior probability of a nondecomposable graphical Gaussian model. Our proposal is based on a new device to sample from Wishart distributions, conditional on the graphical constraints. As a result, our methodology allows Bayesian model selection within the whole class of graphical Gaussian models, including nondecomposable ones. Cited in 10 Documents MSC: 62F15 Bayesian inference 05C90 Applications of graph theory 62D05 Sampling theory, sample surveys Keywords:importance sampling; partial correlation coefficient; sampling from conditional Wishart distibution PDFBibTeX XMLCite \textit{P. Dellaportas} et al., Sankhyā 65, No. 1, 43--55 (2003; Zbl 1192.62090)