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A Note on Sharpe's Algorithm for Minimizing the Sum of Absolute Deviations in a Simple Regression Problem

Author

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  • M. R. Rao

    (University of Rochester)

  • V. Srinivasan

    (University of Rochester)

Abstract

A recent article in this Journal provides an efficient computational scheme for obtaining a regression line that minimizes the sum of absolute deviations of a set of two-dimensional points. The present note interprets that procedure as the solution of the parametric dual to the linear programming formulation of the problem. An alternate and about equally efficient procedure for solving the same problem is also provided.

Suggested Citation

  • M. R. Rao & V. Srinivasan, 1972. "A Note on Sharpe's Algorithm for Minimizing the Sum of Absolute Deviations in a Simple Regression Problem," Management Science, INFORMS, vol. 19(2), pages 222-225, October.
    • Handle: RePEc:inm:ormnsc:v:19:y:1972:i:2:p:222-225
    DOI: 10.1287/mnsc.19.2.222
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    Cited by:

    1. Diaz-Banez, J. M. & Mesa, J. A. & Schobel, A., 2004. "Continuous location of dimensional structures," European Journal of Operational Research, Elsevier, vol. 152(1), pages 22-44, January.
    2. Richard W. Cottle, 2017. "On “Pre-historic” Linear Programming and the Figure of the Earth," Journal of Optimization Theory and Applications, Springer, vol. 175(1), pages 255-277, October.

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