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Subset Regression with Stepwise Directed Search

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  • P. M. T. Broersen

Abstract

Stepwise Directed Search is a combination of forward selection and a modification of backward elimination. Mallows' statistic Cp is used as a criterion function in comparing subsets of different sizes. The method can select automatically the subset with the smallest Cp. Alternatively a number of alternative good candidate subsets of any size can be obtained by using the results of the sweep operator efficiently. This limits the computational effort of subset selection to about three times more than required for estimation without subset selection. Subsets can be selected from any number of regressors, as long as the full set of regression variables can be swept without numerical difficulties. The performance of Stepwise Directed Search on practical data was excellent: it always found the minimum Cp subset and in every example but one it found the best subsets of all sizes.

Suggested Citation

  • P. M. T. Broersen, 1986. "Subset Regression with Stepwise Directed Search," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(2), pages 168-177, June.
    • Handle: RePEc:bla:jorssc:v:35:y:1986:i:2:p:168-177
    DOI: 10.2307/2347267
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    1. Blazy, Régis & Esquerré, Stéphane, 2021. "The CV effect: To what extent does the chance to reorganize depend on a bankruptcy judge’s profile?," International Review of Law and Economics, Elsevier, vol. 66(C).
    2. Régis BLAZY & Stéphane ESQUERRE, 2019. "The CV effect: How far do the chances to reorganize depend on the bankruptcy judges’ profile?," Working Papers of LaRGE Research Center 2019-07, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.

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