Robust Bayesian graphical modeling using Dirichlet \(t\)-distributions

DOI10.1214/13-BA856zbMath1327.62143arXiv1207.1221WikidataQ57566395 ScholiaQ57566395MaRDI QIDQ899035

Mathias Drton, Michael Finegold

Publication date: 21 December 2015

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1207.1221

zbMATH Keywords

Markov chain Monte CarloDirichlet processBayesian inferencegraphical model\(t\)-distribution

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Nonparametric robustness (62G35) Bayesian inference (62F15) Random measures (60G57)

Related Items

Order-invariant prior specification in Bayesian factor analysis, Robust modeling using non-elliptically contoured multivariate \(t\) distributions, Bayesian state space models for dynamic genetic network construction across multiple tissues, Bayesian graphical models for modern biological applications, The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture, Bayesian sparse seemingly unrelated regressions model with variable selection and covariance estimation via the horseshoe+, The Modified-Half-Normal distribution: Properties and an efficient sampling scheme, A horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging, Dependence in elliptical partial correlation graphs, Hierarchical normalized completely random measures for robust graphical modeling, Inferring network structure in non-normal and mixed discrete-continuous genomic data, Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo, Dynamic and robust Bayesian graphical models, On the fractional moments of a truncated centered multivariate normal distribution

Uses Software

• R
• HdBCS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Robust graphical modeling of gene networks using classical and alternative \(t\)-distributions
• An empirical Bayes procedure for the selection of Gaussian graphical models
• Flexible covariance estimation in graphical Gaussian models
• Regularized parameter estimation of high dimensional distribution
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Hyper Markov laws in the statistical analysis of decomposable graphical models
• Sparse graphical models for exploring gene expression data
• Experiments in stochastic computation for high-dimensional graphical models
• A Bayesian analysis of some nonparametric problems
• Objective Bayesian model selection in Gaussian graphical models
• Hierarchical Dirichlet Processes
• Probabilistic Networks and Expert Systems
• Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
• Multivariate T-Distributions and Their Applications
• Bayesian Density Estimation and Inference Using Mixtures
• Decomposable graphical Gaussian model determination
• Simulation of hyper-inverse Wishart distributions in graphical models
• A Monte Carlo method for computing the marginal likelihood in nondecomposable Gaussian graphical models
• Monte Carlo strategies in scientific computing