GVSELECT: Stata module to perform best subsets variable selection

Charles Lindsey () and Simon Sheather
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Simon Sheather: Department of Statistics, Texas A&M University

Statistical Software Components from Boston College Department of Economics

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.

Language: Stata
Requires: Stata version 11.2
Keywords: variable selection; leaps-and-bounds; best subsets; model selection (search for similar items in EconPapers)
Date: 2014-04-13
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.
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http://fmwww.bc.edu/repec/bocode/g/gvselect.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/g/gvselect.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/d/dvisits.dta sample data file (application/x-stata)

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