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ELASTICREGRESS: Stata module to perform elastic net regression, lasso regression, ridge regression

Author

Listed:
  • Wilbur Townsend

    (Stanford University)

Programming Language

Stata

Abstract

elasticregress calculates an elastic net-regularized regression: an estimator of a linear model in which larger parameters are discouraged. This estimator nests the LASSO and the ridge regression, which can be estimated by setting alpha equal to 1 and 0 respectively. lassoregress estimates the LASSO; it is a convenience command equivalent to elasticregress with the option alpha(1). ridgeregress estimates a ridge regression; it is a convenience command equivalent to elasticregress with the option alpha(0). elasticregress implements the coordinate descent algorithm in Friedman, Hastie and Tibshirani (J.Stat.Software, 2008) to produce very efficient estimates of the LASSO, of the ridge regression and of a generalization of the two. The algorithm used is the 'covariance updates' algorithm presented in Section 2 of that paper, except that it does not exploit sparsity in the covariates.

Suggested Citation

  • Wilbur Townsend, 2017. "ELASTICREGRESS: Stata module to perform elastic net regression, lasso regression, ridge regression," Statistical Software Components S458397, Boston College Department of Economics, revised 16 Apr 2018.
    • Handle: RePEc:boc:bocode:s458397
    Note: This module should be installed from within Stata by typing "ssc install elasticregress". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/e/elasticregress.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/e/elasticregress.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/e/elasticregress.ihlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/l/lassoregress.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/l/lassoregress.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/ridgeregress.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/ridgeregress.sthlp
    File Function: help file
    Download Restriction: no
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    Cited by:

    1. Jason T. Kerwin & Rebecca L. Thornton, 2021. "Making the Grade: The Sensitivity of Education Program Effectiveness to Input Choices and Outcome Measures," The Review of Economics and Statistics, MIT Press, vol. 103(2), pages 251-264, May.
    2. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    3. Simon Jäger & Christopher Roth & Nina Roussille & Benjamin Schoefer, 2024. "Worker Beliefs About Outside Options," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1505-1556.
    4. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    5. Du, Shihan & Homrighausen, Pia & Wilke, Ralf A., 2018. "On omitted variables, proxies and unobserved effects in analysis of administrative labour market data," FDZ Methodenreport 201806_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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