Alternative methods of linear regression

Authors:
A. Giloni;M. Padberg
Affiliations:
Sy Syms School of Business, Yeshiva University 500 West 185th Street New York, NY 10033, U.S.A.;Operations Management Department, Stern School of Business New York University, 40 West 4th Street New York, NY 10012, U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2002

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Abstract

This paper is a survey on traditional linear regression techniques using the @?"1-, @?"2-, and @?"~-norm. We derive the characterization of the respective regression estimates (including optimality and uniqueness criteria), as well as discuss some of their statistical properties.