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GVSELECT: Stata module to perform best subsets variable selection

Author

Listed:
  • Charles Lindsey

    (StataCorp LP)

  • Simon Sheather

    (Department of Statistics, Texas A&M University)

Programming Language

Stata

Abstract

gvselect performs best subsets variable selection. The Furnival-Wilson (Technometrics, 1974) leaps-and-bounds algorithm is applied using the log likelihoods of candidate models, allowing variable selection to be performed on a wide family of normal and non-normal regression models. This method is described in Lawless and Singhal (Biometrics, 1978). The log likelihood, Akaike's information criterion, and the Bayesian information criterion are reported for the best regressions at each predictor quantity.

Suggested Citation

  • Charles Lindsey & Simon Sheather, 2014. "GVSELECT: Stata module to perform best subsets variable selection," Statistical Software Components S457816, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s457816
    Note: This module should be installed from within Stata by typing "ssc install gvselect". 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.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/g/gvselect.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/g/gvselect.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/d/dvisits.dta
    File Function: sample data file
    Download Restriction: no
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