Lasso

 
National Institutes of Health

Papers overview

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2016
2016
We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large… (More)
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2015
2015
Ordinary least squares and stepwise selection are widespread in behavioral science research; however, these methods are well… (More)
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Highly Cited
2014
Highly Cited
2014
In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current… (More)
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Highly Cited
2013
Highly Cited
2013
We add a set of convex constraints to the lasso to produce sparse interaction models that honor the hierarchy restriction that an… (More)
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2013
2013
The number of publications performing genome-wide association studies (GWAS) has increased dramatically. Penalized regression… (More)
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2012
2012
We re-examine the original Group Lasso paper of Yuan and Lin (2007). The form of penalty in that paper seems to be designed for… (More)
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Highly Cited
2012
Highly Cited
2012
We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide… (More)
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2010
2010
In this note, we propose the use of sparse methods (e.g. LASSO, Post-LASSO, √ LASSO, and Post√ LASSO) to form first-stage… (More)
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Highly Cited
2010
Highly Cited
2010
We propose a procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for… (More)
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2007
2007
The Genetic Analysis Workshop 15 Problem 3 simulated rheumatoid arthritis data set provided 100 replicates of simulated single… (More)
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