A Monte Carlo Study of Two Robust Alternatives of Least Square Regression Estimation

Richard W. Hill and Paul W. Holland

No 58, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We give some Monte Carlo results on the performance of two robust alternatives to least squares regression estimation - least absolute residuals and the one-step "sine" estimator. We show how to scale the residuals for the sine estimator to achieve constant efficiency at the Gaussian across various choices of X-matrix and give some results for the contaminated Gaussian distribution.

Date: 1974-09
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Published as Hill, Richard W. and Paul W. Holland. "Two Robust Alternatives To Least-Squared Regression," Journal of the American Statistical Association, 1977, v72(360), 828-833.

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