Bayesian Bootstrap Spike-and-Slab LASSO

DOI10.48550/arXiv.2011.14279arXiv2011.14279OpenAlexW4207016985MaRDI QIDQ127195

Lizhen Nie, Veronika Ročková, Lizhen Nie, Veronika Rockova

Publication date: 29 November 2020

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.14279

zbMATH Keywords

posterior contractionBayesian bootstrapweighted likelihood bootstrapSpike-and-Slab LASSO

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Nonparametric Posterior Learning for Emission Tomography ⋮ Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior ⋮ BBSSL

Cites Work

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• Exchangeably weighted bootstraps of the general empirical process
• Bayesian estimation of sparse signals with a continuous spike-and-slab prior
• Bayesian inference and the parametric bootstrap
• Variance prior forms for high-dimensional Bayesian variable selection
• Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies
• Evolutionary stochastic search for Bayesian model exploration
• Particle EM for Variable Selection
• Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO
• Large deviations of the maximum eigenvalue in Wishart random matrices
• The horseshoe estimator for sparse signals
• The Bayesian Lasso
• Bayesian lasso regression
• Bayesian Variable Selection in Linear Regression
• Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
• The Spike-and-Slab LASSO
• Bayesian Model Selection in High-Dimensional Settings
• EMVS: The EM Approach to Bayesian Variable Selection
• Skinny Gibbs: A Consistent and Scalable Gibbs Sampler for Model Selection
• Dirichlet–Laplace Priors for Optimal Shrinkage
• Spike and Slab Gene Selection for Multigroup Microarray Data
• A Useful Convergence Theorem for Probability Distributions
• Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models
• A general theory of concave regularization for high-dimensional sparse estimation problems
• Weighted Bayesian bootstrap for scalable posterior distributions
• Neuronized Priors for Bayesian Sparse Linear Regression

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