Neuronized Priors for Bayesian Sparse Linear Regression (Q6110693)

scientific article; zbMATH DE number 7707792

Language	Label	Description	Also known as
English	Neuronized Priors for Bayesian Sparse Linear Regression	scientific article; zbMATH DE number 7707792

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instance of

scholarly article

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title

Neuronized Priors for Bayesian Sparse Linear Regression (English)

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published in

Journal of the American Statistical Association

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publication date

6 July 2023

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full work available at URL

https://arxiv.org/abs/1810.00141

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https://figshare.com/articles/dataset/Neuronized_Priors_for_Bayesian_Sparse_Linear_Regression/13616658

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zbMATH Keywords

Bayesian shrinkage

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scalable Bayesian computation

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spike-and-slab prior

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variable selection

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MaRDI profile type

MaRDI publication profile

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cites work

Generalized double Pareto shrinkage

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Kernel estimators of asymptotic variance for adaptive Markov chain Monte Carlo

0 references

Posterior model probabilities via path‐based pairwise priors

0 references

Choice of hierarchical priors: Admissibility in estimation of normal means

0 references

Dirichlet–Laplace Priors for Optimal Shrinkage

0 references

Q5657612

0 references

Statistics for high-dimensional data. Methods, theory and applications.

0 references

The horseshoe estimator for sparse signals

0 references

Bayesian linear regression with sparse priors

0 references

Needles and straw in a haystack: posterior concentration for possibly sparse sequences

0 references

Extended Bayesian information criteria for model selection with large model spaces

0 references

On Bayesian model and variable selection using MCMC

0 references

Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models

0 references

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

0 references

Q3172407

0 references

Asymptotic optimality of one-group shrinkage priors in sparse high-dimensional problems

0 references

Reversible jump Markov chain Monte Carlo computation and Bayesian model determination

0 references

Bayesian variable selection regression for genome-wide association studies and other large-scale problems

0 references

Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective

0 references

Shotgun Stochastic Search for “Large<i>p</i>” Regression

0 references

Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization

0 references

Q3543468

0 references

Exploration, normalization, and summaries of high density oligonucleotide array probe level data

0 references

Geometric ergodicity of Metropolis algorithms

0 references

Component-wise Markov chain Monte Carlo: uniform and geometric ergodicity under mixing and composition

0 references

On the use of Non-Local Prior Densities in Bayesian Hypothesis Tests

0 references

Bayesian Model Selection in High-Dimensional Settings

0 references

Fixed-Width Output Analysis for Markov Chain Monte Carlo

0 references

Smoothly Clipped Absolute Deviation on High Dimensions

0 references

Q5405154

0 references

Optimization by Simulated Annealing

0 references

The Collapsed Gibbs Sampler in Bayesian Computations with Applications to a Gene Regulation Problem

0 references

The Multiple-Try Method and Local Optimization in Metropolis Sampling

0 references

Generalised Gibbs sampler and multigrid Monte Carlo for Bayesian computation

0 references

Parameter Expansion for Data Augmentation

0 references

Rates of convergence of the Hastings and Metropolis algorithms

0 references

Bayesian Variable Selection in Linear Regression

0 references

Variance prior forms for high-dimensional Bayesian variable selection

0 references

Bayesian variable selection with shrinking and diffusing priors

0 references

Skinny Gibbs: A Consistent and Scalable Gibbs Sampler for Model Selection

0 references

The Bayesian Lasso

0 references

Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

0 references

Convergence of Slice Sampler Markov Chains

0 references

General state space Markov chains and MCMC algorithms

0 references

Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms

0 references

Bayesian estimation of sparse signals with a continuous spike-and-slab prior

0 references

EMVS: The EM Approach to Bayesian Variable Selection

0 references

The Spike-and-Slab LASSO

0 references

Learning representations by back-propagating errors

0 references

Estimating the dimension of a model

0 references

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

0 references

Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-dimensional Settings

0 references

Nearly optimal Bayesian shrinkage for high-dimensional regression

0 references

On the Geometric Ergodicity of Two-Variable Gibbs Samplers

0 references

Q4864293

0 references

The horseshoe estimator: posterior concentration around nearly black vectors

0 references

Conditions for posterior contraction in the sparse normal means problem

0 references

A majorization-minimization approach to variable selection using spike and slab priors

0 references

Q3802438

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Q5457402

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Identifiers

zbMATH Open document ID

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10.1080/01621459.2021.1876710

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6110693