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Adaptive LAD + LS Regression

In: Adaptive Regression

Author

Listed:
  • Yadolah Dodge

    (University of Neuchâtel)

  • Jana Jureĉková

    (Charles University, Department of Probability and Statistics)

Abstract

Arthanari and Dodge (1981) introduced an estimation method in the linear model based on a convex combination of a least squares and of a least absolute deviations estimators with a fixed weight δ, 0 ≤ δ≤ 1. They also provided two algorithms using a mathematical programming approach for finding estimates in linear regression. However, in optimizing such a convex combination, the experimenter is required to fix the value of δ or vary it at different values up to complete satisfaction in an ad hoc fashion.

Suggested Citation

  • Yadolah Dodge & Jana Jureĉková, 2000. "Adaptive LAD + LS Regression," Springer Books, in: Adaptive Regression, chapter 3, pages 37-60, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4419-8766-2_3
    DOI: 10.1007/978-1-4419-8766-2_3
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