A Metropolis-Hastings based method for sampling from the G-Wishart distribution in Gaussian graphical models

作者：Mitsakakis Nicholas^*; Massam Helene; Escobar Michael D

来源：Electronic Journal of Statistics, 2011, 5: 18-30.

DOI：10.1214/11-EJS594

• Gaussian graphical models
• G-Wishart distribution
• Metropolis-Hastings algorithm
• non-decomposable graphs
• Deviance Information Criterion

In Gaussian graphical models, the conjugate prior for the precision matrix K is called G-Wishart distribution, W-G(delta,D). In this paper we propose a new sampling method for the W-G(delta,D) based on the Metropolis Hastings algorithm and we show its validity through a number of numerical experiments. We show that this method can be easily used to estimate the Deviance Information Criterion, providing with a computationally in-expensive approach for model selection.

• 出版日期2011