Bayesian Graphical Regression
From MaRDI portal
Publication:5229903
DOI10.1080/01621459.2017.1389739zbMath1418.62088OpenAlexW2765396870MaRDI QIDQ5229903
Veerabhadran Baladandayuthapani, Yang Ni, Francesco C. Stingo
Publication date: 19 August 2019
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/2158/1108423
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Bayesian inference (62F15)
Related Items (7)
Graph-valued regression: prediction of unlabelled networks in a non-Euclidean graph space ⋮ Bayesian graphical models for modern biological applications ⋮ High-Dimensional Gaussian Graphical Regression Models with Covariates ⋮ Network Structure Learning Under Uncertain Interventions ⋮ Subject-specific Dirichlet-multinomial regression for multi-district microbiota data analysis ⋮ Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process ⋮ Bayesian network marker selection via the thresholded graph Laplacian Gaussian prior
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
- Non-homogeneous dynamic Bayesian networks for continuous data
- Joint estimation of multiple related biological networks
- Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
- Stratified graphical models -- context-specific independence in graphical models
- Estimating time-varying networks
- Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure
- Time varying undirected graphs
- Spike and slab variable selection: frequentist and Bayesian strategies
- High-dimensional graphs and variable selection with the Lasso
- Knowledge representation and inference in similarity networks and Bayesian multinets
- Bayesian nonlinear model selection for gene regulatory networks
- Objective Bayesian Search of Gaussian Directed Acyclic Graphical Models for Ordered Variables with Non‐Local Priors
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Joint estimation of multiple graphical models
- A sparse ising model with covariates
- Semiparametric Regression
- On the use of Non-Local Prior Densities in Bayesian Hypothesis Tests
- Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-dimensional Settings
- Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models
- Bayesian Model Selection in High-Dimensional Settings
- EMVS: The EM Approach to Bayesian Variable Selection
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Bayesian Inference of Multiple Gaussian Graphical Models
- Efficient local updates for undirected graphical models
This page was built for publication: Bayesian Graphical Regression