Disjunct support spike-and-slab priors for variable selection in regression under quasi-sparseness

Cites Work

Title not available (Why is that?)
Title not available (Why is that?)
Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
Bayesian variable selection with shrinking and diffusing priors
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
Criteria for Bayesian model choice with application to variable selection
Estimating the dimension of a model
Least angle regression. (With discussion)
High-dimensional posterior consistency for hierarchical non-local priors in regression
Comparison of Bayesian predictive methods for model selection
An exploration of aspects of Bayesian multiple testing
Spike and slab variable selection: frequentist and Bayesian strategies
Marginal Likelihood from the Gibbs Output
Extended Bayesian information criteria for model selection with large model spaces
The horseshoe estimator for sparse signals
Mixtures of g Priors for Bayesian Variable Selection
Bayesian Model Averaging for Linear Regression Models
On the use of Non-Local Prior Densities in Bayesian Hypothesis Tests
Stability Selection
The Spike-and-Slab LASSO
Marginal Likelihood From the Metropolis–Hastings Output
Bayesian Model Selection in High-Dimensional Settings
On Sampling Strategies in Bayesian Variable Selection Problems With Large Model Spaces
EMVS: The EM Approach to Bayesian Variable Selection
Scalable Importance Tempering and Bayesian Variable Selection
Robust Bayesian Inference via Coarsening
Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective
Benchmark priors for Bayesian model averaging.

This page was built for publication: Disjunct support spike-and-slab priors for variable selection in regression under quasi-sparseness

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6541607)