BDgraph-package: Graph selection based on birth-death MCMC

Description

The R package BDgraph is a statistical tool for Bayesian model selection in undirected Gaussian graphical models based on birth-death MCMC methodology.

Arguments

Details

This package provides an implementation of the procedures described in Mohammadi and Wit (2012). The main function is 'bdgraph' which is birth-death MCMC algorithm for Bayesian model selection in Gaussian graphical models. Functions: bdgraph Graph selection based on birth-death MCMC algorithm bdgraph.sim Data generator according to graph structure bdgraph.npt Nonparametric transfer compare Comparing the result I.g Normalizing constant of G-Wishart distribution phat Posterior edge inclusion probabilities plot.bdgraph Plot function for "bdgraph" output plotcoda Convergency plots print.bdgraph Print function for "bdgraph" output prob Posterior probabilities of the graphs rGWishart Sampling from G-Wishart distribution select Selecting the best graphs CellSignal A flow cytometry dataset summary.bdgraph Summary function for "bdgraph" output traceplot Trace plot of graph size from "bdgraph" output

References

Mohammadi, A. and E. C. Wit (2012). Gaussian graphical model determination based on birth-death MCMC inference, arXiv:1210.5371v4. http://arxiv.org/abs/1210.5371v4 Atay-Kayis, A. and H. Massam (2005). A Monte Carlo method for computing the marginal likelihood in nondecomposable Gaussian graphical models. Biometrika 92(2), 317-335. Wang, H. and S. Li (2012). Efficient Gaussian graphical model determination under G-Wishart prior distributions. Electronic Journal of Statistics 6, 168-198.