Random weighting in LASSO regression

DOI10.1214/22-EJS2020zbMath1493.62119arXiv2002.02629OpenAlexW3139927404MaRDI QIDQ2154956

Michael A. Newton, Tun Lee Ng

Publication date: 15 July 2022

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.02629

zbMATH Keywords

bootstrapconsistencyLASSOmodel selection consistencyrandom weightsweighted likelihood bootstrapperturbation bootstrapweighted Bayesian bootstrap

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian inference (62F15) Bootstrap, jackknife and other resampling methods (62F40)

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Uses Software

• R
• Monomvn

Cites Work

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• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Bayesian variable selection with shrinking and diffusing priors
• The Adaptive Lasso and Its Oracle Properties
• Strong consistency of Lasso estimators
• Asymptotic properties of Lasso+mLS and Lasso+Ridge in sparse high-dimensional linear regression
• Bayesian linear regression with sparse priors
• A rank statistics approach to the consistency of a general bootstrap
• Generalized bootstrap for estimating equations
• Asymptotics for Lasso-type estimators.
• The Lasso problem and uniqueness
• Least squares after model selection in high-dimensional sparse models
• Perturbation bootstrap in adaptive Lasso
• A simple resampling method by perturbing the minimand
• Asymptotic properties of the residual bootstrap for Lasso estimators
• Bootstrapping Lasso Estimators
• Statistical Analysis of Financial Data in S-Plus
• A Perturbation Method for Inference on Regularized Regression Estimates
• On the validity of the pairs bootstrap for lasso estimators
• The Bayesian Lasso
• On Deriving the Inverse of a Sum of Matrices
• Strong consistency of least squares estimates in multiple regression
• Mathematical Statistics
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Bayesian Model Selection in High-Dimensional Settings
• General Bayesian updating and the loss-likelihood bootstrap
• Distributional consistency of the lasso by perturbation bootstrap
• A General Framework for Updating Belief Distributions
• Probability
• Weighted Bayesian bootstrap for scalable posterior distributions