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The Spike-and-Slab LASSO (Q4690970)

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scientific article; zbMATH DE number 6962803

Language	Label	Description	Also known as
English	The Spike-and-Slab LASSO	scientific article; zbMATH DE number 6962803

Statements

scholarly article

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The Spike-and-Slab LASSO (English)

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Veronika Rockova

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Edward I. George

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Journal of the American Statistical Association

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publication date

23 October 2018

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zbMATH Keywords

high-dimensional regression

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LASSO

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penalized likelihood

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posterior concentration

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spike-and-slab

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variable selection

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1080/01621459.2016.1260469

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Dirichlet–Laplace Priors for Optimal Shrinkage

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Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

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

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Enhancing sparsity by reweighted \(\ell _{1}\) minimization

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The horseshoe estimator for sparse signals

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Bayesian linear regression with sparse priors

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

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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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Asymptotic properties for combined L1 and concave regularization

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Algebraic Evaluations of Some Euler Integrals, Duplication Formulae for Appell's Hypergeometric Function <i>F</i><sub>1</sub>, and Brownian Variations

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Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences

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Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector

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<i>SparseNet</i>: Coordinate Descent With Nonconvex Penalties

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Posterior model consistency in variable selection as the model dimension grows

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EMVS: The EM Approach to Bayesian Variable Selection

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Bayesian Penalty Mixing: The Case of a Non-separable Penalty

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Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models

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

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Thresholding-based iterative selection procedures for model selection and shrinkage

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SLOPE is adaptive to unknown sparsity and asymptotically minimax

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The horseshoe estimator: posterior concentration around nearly black vectors

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Optimal computational and statistical rates of convergence for sparse nonconvex learning problems

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A general theory of concave regularization for high-dimensional sparse estimation problems

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Nearly unbiased variable selection under minimax concave penalty

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The Adaptive Lasso and Its Oracle Properties

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One-step sparse estimates in nonconcave penalized likelihood models

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Identifiers

zbMATH Open document ID

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10.1080/01621459.2016.1260469

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:4690970

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