A Procedure for Optimal Stepwise MSAE Regression Analysis

Gary M. Roodman
Additional contact information
Gary M. Roodman: Dartmouth College, Hanover, New Hampshire

Operations Research, 1974, vol. 22, issue 2, 393-399

Abstract: This paper brings together two topics from regression analysis. One is the topic of stepwise regression, a set of commonly used procedures for exploring alternative formulations of the regression model. The other topic is regression by minimizing the sum of the absolute errors about the regression line (MSAE). This technique has been found, in a variety of circumstances, to be more attractive than the traditional least-squares method. The paper presents a procedure for selecting from among m regressors the best sets of k , k + 1, … and m regressors according to the MSAE criterion ( k ≦ m ). Building upon the well known linear-programming formulation of the MSAE problem, the paper develops a partial enumerative search scheme, in which a set of distinct, but related, combinatorial optimization problems (corresponding to determination of “best k ,” “best k + 1,” etc.) are, in effect, solved simultaneously.

Date: 1974
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.22.2.393 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:22:y:1974:i:2:p:393-399

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().