Pages that link to "Item:Q3399065"
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The following pages link to Objective Bayesian model selection in Gaussian graphical models (Q3399065):
Displaying 46 items.
- Bayesian structure learning in sparse Gaussian graphical models (Q273578) (← links)
- Bayesian state space models for dynamic genetic network construction across multiple tissues (Q309414) (← links)
- Modeling dependent gene expression (Q439142) (← links)
- Bayesian high-dimensional screening via MCMC (Q466528) (← links)
- Posterior convergence rates for estimating large precision matrices using graphical models (Q470497) (← links)
- Credal model averaging for classification: representing prior ignorance and expert opinions (Q473394) (← links)
- Bayesian sparse graphical models for classification with application to protein expression data (Q484003) (← links)
- Bayesian graphical models for differential pathways (Q516442) (← links)
- Learning Gaussian graphical models with fractional marginal pseudo-likelihood (Q518603) (← links)
- Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem (Q605920) (← links)
- An empirical Bayes procedure for the selection of Gaussian graphical models (Q693346) (← links)
- Constructing priors based on model size for nondecomposable Gaussian graphical models: a simulation based approach (Q716165) (← links)
- Robust Bayesian graphical modeling using Dirichlet \(t\)-distributions (Q899035) (← links)
- The performance of covariance selection methods that consider decomposable models only (Q899046) (← links)
- Nonparametric Bayesian multiple testing for longitudinal performance stratification (Q965133) (← links)
- Asymptotics of Bayesian median loss estimation (Q990880) (← links)
- Prior distributions for objective Bayesian analysis (Q1631565) (← links)
- Objective Bayesian comparison of constrained analysis of variance models (Q1682437) (← links)
- Efficient Bayesian regularization for graphical model selection (Q1738143) (← links)
- Hierarchical Gaussian graphical models: beyond reversible jump (Q1950899) (← links)
- Penalized model-based clustering with unconstrained covariance matrices (Q1952033) (← links)
- Bayesian inference for high-dimensional decomposable graphs (Q2044345) (← links)
- High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood (Q2058896) (← links)
- Objective Bayesian edge screening and structure selection for Ising networks (Q2141635) (← links)
- Bayesian graphical models for modern biological applications (Q2152185) (← links)
- Contraction of a quasi-Bayesian model with shrinkage priors in precision matrix estimation (Q2156815) (← links)
- Consistent Bayesian sparsity selection for high-dimensional Gaussian DAG models with multiplicative and beta-mixture priors (Q2196119) (← links)
- Bayesian graph selection consistency under model misspecification (Q2214264) (← links)
- On the Letac-Massam conjecture and existence of high dimensional Bayes estimators for graphical models (Q2293718) (← links)
- A review of Gaussian Markov models for conditional independence (Q2301082) (← links)
- Modeling association in microbial communities with clique loglinear models (Q2318667) (← links)
- Sparse seemingly unrelated regression modelling: applications in finance and econometrics (Q2445741) (← links)
- Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis (Q2846452) (← links)
- Objective Bayesian search of Gaussian directed acyclic graphical models for ordered variables with non-local priors (Q2846456) (← links)
- Objective Bayes Factors for Gaussian Directed Acyclic Graphical Models (Q3145566) (← links)
- An Objective Bayesian Criterion to Determine Model Prior Probabilities (Q3460655) (← links)
- On Sampling Strategies in Bayesian Variable Selection Problems With Large Model Spaces (Q4916951) (← links)
- Bayesian model selection in complex linear systems, as illustrated in genetic association studies (Q4979229) (← links)
- (Q4998947) (← links)
- Bayesian Regularization for Graphical Models With Unequal Shrinkage (Q5242470) (← links)
- On the non-local priors for sparsity selection in high-dimensional Gaussian DAG models (Q5880097) (← links)
- Objective methods for graphical structural learning (Q6067698) (← links)
- Covariance structure estimation with Laplace approximation (Q6074739) (← links)
- A loss‐based prior for Gaussian graphical models (Q6081851) (← links)
- Calibrated Bayes factors under flexible priors (Q6091268) (← links)
- Bayesian sparse graphical models and their mixtures (Q6537781) (← links)
