SUBSET: Stata module to implement best covariates and stepwise subset selection

Giovanni Cerulli

Statistical Software Components from Boston College Department of Economics

Abstract: subset is a Stata wrapper for the R function "regsubsets()", providing "best", "backward", and "forward" stepwise subset covariates selection, a Machine Learning approach to select the optimal number of features (covariates) in a supervised linear learning approach (i.e. a linear regression model) with many covariates. The "forward" model can be also used when p (the number of covariates) is larger than N (the sample size). This method provides both the optimal subset of covariates for each specific size of the model (i.e., size=1 covariates, size=2 covariates, etc.), and the overall optimal size. The latter one is found using three criteria as validation approaches: Adjusted R2, CP, and BIC.

Language: Stata
Requires: Stata version 15 and R
Keywords: subset; regression; covariates; machine learning (search for similar items in EconPapers)
Date: 2019-05-07, Revised 2022-12-06
Note: This module should be installed from within Stata by typing "ssc install subset". 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/s/subset.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/s/subset.sthlp help file (text/plain)

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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s458647

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