Model selection in high-dimensional noisy data: a simulation study

DOI10.1080/00949655.2019.1607345OpenAlexW2938637991WikidataQ128016170 ScholiaQ128016170MaRDI QIDQ5107440

Magne Thoresen, Giovanni Romeo

Publication date: 27 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: http://urn.nb.no/URN:NBN:no-78444

zbMATH Keywords

measurement errorvariable selectionhigh-dimensional regressionLassomatrix uncertainty selectorconvex conditional Lasso

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Screening Methods for Linear Errors-in-Variables Models in High Dimensions ⋮ Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method

Uses Software

• BGX

Cites Work

• Unnamed Item
• Unnamed Item
• Measurement error in Lasso: impact and likelihood bias correction
• Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• The Adaptive Lasso and Its Oracle Properties
• Sparse recovery under matrix uncertainty
• CoCoLasso for high-dimensional error-in-variables regression
• High-dimensional regression with noisy and missing data: provable guarantees with nonconvexity
• Least angle regression. (With discussion)
• Simultaneous analysis of Lasso and Dantzig selector
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Consensus-Based Distributed Total Least Squares Estimation in Ad Hoc Wireless Sensor Networks
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Measurement Error in Nonlinear Models
• Improved matrix uncertainty selector
• BGX: a fully Bayesian integrated approach to the analysis of Affymetrix GeneChip data
• Error Distribution for Gene Expression Data
• Exploration, normalization, and summaries of high density oligonucleotide array probe level data
• Bayesian Error‐in‐Variable Survival Model for the Analysis of GeneChip Arrays
• Linear and Conic Programming Estimators in High Dimensional Errors-in-variables Models

This page was built for publication: Model selection in high-dimensional noisy data: a simulation study