The use of vector bootstrapping to improve variable selection precision in Lasso models
From MaRDI portal
Publication:309418
DOI10.1515/sagmb-2015-0043zbMath1344.92011OpenAlexW2500477403WikidataQ39719365 ScholiaQ39719365MaRDI QIDQ309418
Dorret Boomsma, Charles Laurin, Gitta H. Lubke
Publication date: 7 September 2016
Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc5131926
Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Bootstrap, jackknife and other resampling methods (62F40)
Uses Software
Cites Work
- Statistics for high-dimensional data. Methods, theory and applications.
- On the distribution of penalized maximum likelihood estimators: the LASSO, SCAD, and thresholding
- Genomic control, a new approach to genetic-based association studies.
- Asymptotics for Lasso-type estimators.
- Least angle regression. (With discussion)
- The Lasso problem and uniqueness
- Discussion: ``A significance test for the lasso
- Rejoinder: ``A significance test for the lasso
- Model selection via multifold cross validation
- Pathwise coordinate optimization
- Penalized regression, standard errors, and Bayesian Lassos
- Bootstrapping Lasso Estimators
- A Perturbation Method for Inference on Regularized Regression Estimates
- On the validity of the pairs bootstrap for lasso estimators
- A generalized Dantzig selector with shrinkage tuning
- Model Selection: An Integral Part of Inference
- Stability Selection
- Regression Shrinkage and Selection via The Lasso: A Retrospective
- Variance Estimation Using Refitted Cross-Validation in Ultrahigh Dimensional Regression
- Note on “Comparison of Model Selection for Regression” by Vladimir Cherkassky and Yunqian Ma
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: The use of vector bootstrapping to improve variable selection precision in Lasso models
