Bayesian estimation of sparse signals with a continuous spike-and-slab prior
From MaRDI portal
Publication:1747745
DOI10.1214/17-AOS1554zbMath1395.62230OpenAlexW2788365376MaRDI QIDQ1747745
Publication date: 27 April 2018
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/17-aos1554
Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian inference (62F15) Linear inference, regression (62J99) Empirical decision procedures; empirical Bayes procedures (62C12)
Related Items (41)
On minimax optimality of sparse Bayes predictive density estimates ⋮ Bayesian Estimation of Gaussian Conditional Random Fields ⋮ Conditions for posterior contraction in the sparse normal means problem ⋮ Bayesian regularization of Gaussian graphical models with measurement error ⋮ Joint analysis of semicontinuous data with latent variables ⋮ Prior distributions for objective Bayesian analysis ⋮ Optimal Bayesian minimax rates for unconstrained large covariance matrices ⋮ Objective Bayesian edge screening and structure selection for Ising networks ⋮ Contraction of a quasi-Bayesian model with shrinkage priors in precision matrix estimation ⋮ Adaptive Bayesian SLOPE: Model Selection With Incomplete Data ⋮ Bayesian linear regression for multivariate responses under group sparsity ⋮ Optimal convergence rates of Bayesian wavelet estimation with a novel empirical prior in nonparametric regression model ⋮ Optimal false discovery control of minimax estimators ⋮ Neuronized Priors for Bayesian Sparse Linear Regression ⋮ Consistent Sparse Deep Learning: Theory and Computation ⋮ Bayesian nonparametric hypothesis testing for longitudinal data analysis ⋮ Bayesian sparse spiked covariance model with a continuous matrix shrinkage prior ⋮ Unnamed Item ⋮ A Bayesian method for estimating gene‐level polygenicity under the framework of transcriptome‐wide association study ⋮ The Median probability model and correlated variables ⋮ Fast exact Bayesian inference for sparse signals in the normal sequence model ⋮ Semiparametric functional factor models with Bayesian rank selection ⋮ Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models ⋮ Empirical Bayes analysis of spike and slab posterior distributions ⋮ Spike-and-slab Lasso biclustering ⋮ Maximum pairwise Bayes factors for covariance structure testing ⋮ Bayesian estimation of sparse signals with a continuous spike-and-slab prior ⋮ Spike and slab empirical Bayes sparse credible sets ⋮ Needles and straw in a haystack: robust confidence for possibly sparse sequences ⋮ Bayesian Bootstrap Spike-and-Slab LASSO ⋮ Variance prior forms for high-dimensional Bayesian variable selection ⋮ Unified Bayesian theory of sparse linear regression with nuisance parameters ⋮ Adaptive Bayesian nonparametric regression using a kernel mixture of polynomials with application to partial linear models ⋮ Bayesian variable selection for logistic regression ⋮ Bayesian effect selection in structured additive distributional regression models ⋮ Dynamic variable selection with spike-and-slab process priors ⋮ Ultra high-dimensional multivariate posterior contraction rate under shrinkage priors ⋮ Comment: ``Bayes, oracle Bayes and empirical Bayes ⋮ Bayesian Regularization for Graphical Models With Unequal Shrinkage ⋮ Rates of contraction with respect to \(L_2\)-distance for Bayesian nonparametric regression ⋮ Particle EM for Variable Selection
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A unified approach to model selection and sparse recovery using regularized least squares
- Bayesian variable selection with shrinking and diffusing priors
- The Adaptive Lasso and Its Oracle Properties
- SLOPE is adaptive to unknown sparsity and asymptotically minimax
- Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector
- The horseshoe estimator: posterior concentration around nearly black vectors
- Statistics for high-dimensional data. Methods, theory and applications.
- Consistency of spike and slab regression
- Bayesian linear regression with sparse priors
- The sparsity and bias of the LASSO selection in high-dimensional linear regression
- Bayesian estimation of sparse signals with a continuous spike-and-slab prior
- Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
- Needles and straw in a haystack: posterior concentration for possibly sparse sequences
- Spike and slab variable selection: frequentist and Bayesian strategies
- Simultaneous analysis of Lasso and Dantzig selector
- On optimality of Bayesian testimation in the normal means problem
- Posterior contraction in sparse Bayesian factor models for massive covariance matrices
- Empirical Bayes selection of wavelet thresholds
- Calibration and empirical Bayes variable selection
- The horseshoe estimator for sparse signals
- Bayesian Variable Selection in Linear Regression
- Ideal spatial adaptation by wavelet shrinkage
- Prediction Via Orthogonalized Model Mixing
- Regularization of Wavelet Approximations
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Detecting Differentially Expressed Genes in Microarrays Using Bayesian Model Selection
- Sparsity and Smoothness Via the Fused Lasso
- The Spike-and-Slab LASSO
- EMVS: The EM Approach to Bayesian Variable Selection
- Regularization and Variable Selection Via the Elastic Net
- Dirichlet–Laplace Priors for Optimal Shrinkage
This page was built for publication: Bayesian estimation of sparse signals with a continuous spike-and-slab prior