Regression Shrinkage and Selection Via the Lasso

JOURNAL ARTICLE published 1 January 1996 in Journal of the Royal Statistical Society Series B: Statistical Methodology

Authors: Robert Tibshirani

Regression Shrinkage and Selection via The Lasso: A Retrospective

JOURNAL ARTICLE published 1 June 2011 in Journal of the Royal Statistical Society Series B: Statistical Methodology

Authors: Robert Tibshirani

Figure 2: Radiomics features are selected via least absolute shrinkage and selection operator (LASSO) logistic regression.

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Figure 2: Predictors selection based on the least absolute shrinkage and selection operator (LASSO) regression method.

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Figure 1: Feature selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model.

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Figure 2: Feature selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model.

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Forward stagewise regression and the monotone lasso

JOURNAL ARTICLE published 1 January 2007 in Electronic Journal of Statistics

Authors: Trevor Hastie | Jonathan Taylor | Robert Tibshirani | Guenther Walther

Figure 2: The least absolute shrinkage and selection operator (LASSO) regression algorithm for radiomics feature selection and radiomics signature construction.

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THE LASSO METHOD FOR VARIABLE SELECTION IN THE COX MODEL

JOURNAL ARTICLE published 28 February 1997 in Statistics in Medicine

Authors: ROBERT TIBSHIRANI

Exact post-selection inference for the generalized lasso path

JOURNAL ARTICLE published 1 January 2018 in Electronic Journal of Statistics

Authors: Sangwon Hyun | Max G’Sell | Ryan J. Tibshirani

An Ordered Lasso and Sparse Time-Lagged Regression

JOURNAL ARTICLE published 1 October 2016 in Technometrics

Authors: Robert Tibshirani | Xiaotong Suo

A significance test for the lasso

JOURNAL ARTICLE published 1 April 2014 in The Annals of Statistics

Authors: Richard Lockhart | Jonathan Taylor | Ryan J. Tibshirani | Robert Tibshirani

Rejoinder: “A significance test for the lasso”

JOURNAL ARTICLE published 1 April 2014 in The Annals of Statistics

Authors: Richard Lockhart | Jonathan Taylor | Ryan J. Tibshirani | Robert Tibshirani

Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons

JOURNAL ARTICLE published 1 November 2020 in Statistical Science

Authors: Trevor Hastie | Robert Tibshirani | Ryan Tibshirani

The lasso problem and uniqueness

JOURNAL ARTICLE published 1 January 2013 in Electronic Journal of Statistics

Authors: Ryan J. Tibshirani

Correction to rejoinder to “A significance test for the Lasso”

JOURNAL ARTICLE published 1 October 2014 in The Annals of Statistics

Authors: Richard Lockhart | Jonathan Taylor | Ryan J. Tibshirani | Robert Tibshirani

Rejoinder: Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons

JOURNAL ARTICLE published 1 November 2020 in Statistical Science

Authors: Trevor Hastie | Robert Tibshirani | Ryan J. Tibshirani

Table 3: The least absolute shrinkage and selection operator (LASSO)-Cox regression model to further select prognostic predictor of disease-free survival and overall survival.

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Degrees of freedom in lasso problems

JOURNAL ARTICLE published 1 April 2012 in The Annals of Statistics

Authors: Ryan J. Tibshirani | Jonathan Taylor

A lasso for hierarchical interactions

JOURNAL ARTICLE published 1 June 2013 in The Annals of Statistics

Authors: Jacob Bien | Jonathan Taylor | Robert Tibshirani