Fast exact Bayesian inference for sparse signals in the normal sequence model

DOI10.1214/20-ba1227arXiv1810.10883OpenAlexW3046972439MaRDI QIDQ6201433

Tim van Erven, Botond Szabó

Publication date: 20 February 2024

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1810.10883

zbMATH Keywords

model selectionhigh-dimensional statisticsspike-and-slab prior

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Statistics (62-XX)

Related Items (1)

On minimax optimality of sparse Bayes predictive density estimates

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector
• The horseshoe estimator: posterior concentration around nearly black vectors
• Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
• Criteria for Bayesian model choice with application to variable selection
• De Finetti's theorem for abstract finite exchangeable sequences
• Bayesian linear regression with sparse priors
• Finite exchangeable sequences
• Uncertainty quantification for the horseshoe (with discussion)
• Empirical Bayes analysis of spike and slab posterior distributions
• Bayesian estimation of sparse signals with a continuous spike-and-slab prior
• Reconstruction of sparse vectors in white Gaussian noise
• 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 empirical Bayes sparse credible sets
• Needles and straw in a haystack: robust confidence for possibly sparse sequences
• An exploration of aspects of Bayesian multiple testing
• Adaptive posterior contraction rates for the horseshoe
• Adapting to unknown sparsity by controlling the false discovery rate
• Fast multiplication of large numbers
• Proximal Markov chain Monte Carlo algorithms
• Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies
• The horseshoe estimator for sparse signals
• Mixtures of g Priors for Bayesian Variable Selection
• Bayesian Variable Selection in Linear Regression
• Accuracy and Stability of Numerical Algorithms
• EMVS: The EM Approach to Bayesian Variable Selection
• The Moment Problem
• Universal Codes From Switching Strategies
• OUP accepted manuscript
• THE TRANSFORMATION OF POISSON, BINOMIAL AND NEGATIVE-BINOMIAL DATA
• Transformations Related to the Angular and the Square Root
• Benchmark priors for Bayesian model averaging.
• Gaussian model selection

This page was built for publication: Fast exact Bayesian inference for sparse signals in the normal sequence model