Weak signal identification and inference in penalized model selection

DOI10.1214/16-AOS1482zbMath1371.62025arXiv1611.04638OpenAlexW2544825179MaRDI QIDQ2012934

Peibei Shi, Annie Qu

Publication date: 3 August 2017

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.04638

zbMATH Keywords

model selectionadaptive Lassofinite sample inferenceweak signal

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric inference under constraints (62F30)

Related Items (5)

A weak‐signal‐assisted procedure for variable selection and statistical inference with an informative subsample ⋮ Weak Signal Identification and Inference in Penalized Likelihood Models for Categorical Responses ⋮ Linear and nonlinear signal detection and estimation in high-dimensional nonparametric regression under weak sparsity ⋮ A Bootstrap Lasso + Partial Ridge Method to Construct Confidence Intervals for Parameters in High-dimensional Sparse Linear Models ⋮ Nonparametric independence feature screening for ultrahigh-dimensional survival data

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