An empirical threshold of selection probability for analysis of high-dimensional correlated data

DOI10.1080/00949655.2020.1739286OpenAlexW3011213073MaRDI QIDQ5036882

Hokeun Sun, Kipoong Kim, Jajoon Koo

Publication date: 23 February 2022

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

Full work available at URL: https://doi.org/10.1080/00949655.2020.1739286

zbMATH Keywords

regularizationvariable selectiontuning parameterselection probabilityempirical threshold

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Statistics (62-XX)

Uses Software

• glmnet

Cites Work

• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Variable selection and regression analysis for graph-structured covariates with an application to genomics
• Replication in genome-wide association studies
• Coordinate descent algorithms for lasso penalized regression
• Stability Selection
• Variable Selection with Error Control: Another Look at Stability Selection
• Regularization and Variable Selection Via the Elastic Net
• Model Selection and Estimation in Regression with Grouped Variables

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