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KRLS: Stata module to perform Kernel–Based Regularized Least Squares

Author

Listed:
  • Jeremy Ferwerda

    (MIT)

  • Jens Hainmueller

    (Stanford University)

  • Chad Hazlett

    (MIT)

Programming Language

Stata

Abstract

krls implements Kernel-Based Regularized Least Squares (KRLS), a machine learning method described in Hainmueller and Hazlett (2013) that allows users to solve regression and classification problems without manual specification search and strong functional form assumptions. The flexible KRLS estimator learns the functional form from the data and thereby protects inferences against misspecification bias. Yet, it nevertheless allows for interpretability and inference in ways similar to ordinary regression models. In particular, KRLS provides closed-form estimates for the predicted values, variances, and the pointwise partial derivatives that characterize the marginal effects of each independent variable at each data point in the covariate space. KRLS is thus a convenient and powerful alternative for problems requiring regression-based analyses. For more information see Jeremy Ferwerda, Jens Hainmueller, Chad J. Hazlett (2017). Kernel-Based Regularized Least Squares in R (KRLS) and Stata (krls) Journal of Statistical Software, 79(3), 1-26. doi:10.18637/jss.v079.i03

Suggested Citation

  • Jeremy Ferwerda & Jens Hainmueller & Chad Hazlett, 2013. "KRLS: Stata module to perform Kernel–Based Regularized Least Squares," Statistical Software Components S457704, Boston College Department of Economics, revised 06 Mar 2015.
    • Handle: RePEc:boc:bocode:s457704
    Note: This module should be installed from within Stata by typing "ssc install krls". 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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    File URL: http://fmwww.bc.edu/repec/bocode/k/krls.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/k/krls.sthlp
    File Function: help file
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    File URL: http://fmwww.bc.edu/repec/bocode/k/krls_p.ado
    File Function: program code
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    File URL: http://fmwww.bc.edu/repec/bocode/g/growthdata.dta
    File Function: sample data file
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    Cited by:

    1. Prehn, S. & Glauben, T. & Loy, J.-P., 2016. "Demand-Driven Markets and the Importance of Demand Rationing," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 51, March.

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