articleTop 1% cited
Regression Shrinkage and Selection via The Lasso: A Retrospective
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2011 · Vol. 73(3) · pp. 273–282
Robert Tibshirani✉(Stanford University)
Abstract
Summary In the paper I give a brief review of the basic idea and some history and then discuss some developments since the original paper on regression shrinkage and selection via the lasso.
Statistical Methods and InferenceControl Systems and IdentificationAdvanced Statistical Methods and ModelsLasso (programming language)ShrinkageSelection (genetic algorithm)RegressionRegression analysisComputer scienceArtificial intelligenceStatisticsEconometricsMachine learning
Funding
- Royal Society
Citations
3,604
FWCI
178.85
field-weighted impact
References
91
Percentile
100%
vs. same field & year
Citations per year
Cited by
Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease
IEEE Transactions on Biomedical Engineering · 2012 · 706 citations
Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems
BMC Bioinformatics · 2011 · 980 citations
Towards better clinical prediction models: seven steps for development and an ABCD for validation
European Heart Journal · 2014 · 1,814 citations
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
Journal of Medical Internet Research · 2016 · 1,002 citations
References
Nearly unbiased variable selection under minimax concave penalty
The Annals of Statistics · 2010 · 3,900 citations
High-dimensional graphs and variable selection with the Lasso
The Annals of Statistics · 2006 · 2,433 citations
The Adaptive Lasso and Its Oracle Properties
Journal of the American Statistical Association · 2006 · 7,497 citations
Least angle regression
The Annals of Statistics · 2004 · 9,400 citations
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Journal of the American Statistical Association · 2001 · 9,035 citations
Model selection and estimation in the Gaussian graphical model
Biometrika · 2007 · 1,693 citations
Stable recovery of sparse overcomplete representations in the presence of noise
IEEE Transactions on Information Theory · 2005 · 2,215 citations
The Group Lasso for Logistic Regression
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2008 · 1,692 citations
Related articles
Regression Shrinkage and Selection via The Lasso: A Retrospective
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2011 · 3,604 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.